{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 1 - Model Training\n",
    "\n",
    "Now that we have a feel for the data we are dealing with, we can start designing our model. In this notebook, we will define the network architecture and train the model. We will also discuss some of the transformations on the data in response to observations that we made in the data exploration section of the notebook.\n",
    "\n",
    "Let us start by importing some libraries and defining some paths."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "from keras.models import Sequential, Model\n",
    "from keras.layers import Conv2D, MaxPooling2D, Dropout, Flatten, Dense, Lambda, Input, concatenate\n",
    "from keras.layers.normalization import BatchNormalization\n",
    "from keras.layers.advanced_activations import ELU\n",
    "from keras.optimizers import Adam, SGD, Adamax, Nadam\n",
    "from keras.callbacks import ReduceLROnPlateau, ModelCheckpoint, CSVLogger, EarlyStopping\n",
    "import keras.backend as K\n",
    "from keras.preprocessing import image\n",
    "\n",
    "from keras_tqdm import TQDMNotebookCallback\n",
    "\n",
    "import json\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from Generator import DriveDataGenerator\n",
    "from Cooking import checkAndCreateDir\n",
    "import h5py\n",
    "from PIL import Image, ImageDraw\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# << The directory containing the cooked data from the previous step >>\n",
    "COOKED_DATA_DIR = 'data_cooked/'\n",
    "\n",
    "# << The directory in which the model output will be placed >>\n",
    "MODEL_OUTPUT_DIR = 'model'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's read in the datasets from the exploration phase. If these do not exist, run the snippet from the [previous](DataExplorationAndPreparation.ipynb) notebook to generate them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = h5py.File(os.path.join(COOKED_DATA_DIR, 'train.h5'), 'r')\n",
    "eval_dataset = h5py.File(os.path.join(COOKED_DATA_DIR, 'eval.h5'), 'r')\n",
    "test_dataset = h5py.File(os.path.join(COOKED_DATA_DIR, 'test.h5'), 'r')\n",
    "\n",
    "num_train_examples = train_dataset['image'].shape[0]\n",
    "num_eval_examples = eval_dataset['image'].shape[0]\n",
    "num_test_examples = test_dataset['image'].shape[0]\n",
    "\n",
    "batch_size=32"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For image data, it is too expensive to load the entire dataset into memory. Fortunatly, Keras has the concept of DataGenerators. A DataGenerator is nothing more than an iterator that will read data from disk in chunks. This allows you to keep both your CPU and GPU busy, increasing throughput. \n",
    "\n",
    "We made a few observations during the exploration phase. Now let's come up with a strategy to incorporate them in our training algorithm:\n",
    "* **Only a small portion of the image is of interest** - when generating batches, we can remove the pieces of the image that are not of interest.\n",
    "* **The dataset exhibits vertical flip tolerance** - when generating batches, we can randomly flip some images and labels around the Y axis so the model has new data to learn from.\n",
    "* **The dataset should be invariant to changes in lighting** - when generating batches, we can randomly add or remove brightness from the images so the model can learn that global changes in lighting should be ignored.\n",
    "* **The dataset has a high proportion of zero-valued images** - when generating batches, we can randomly drop a percentage of data points where the steering angle is zero so the model sees a balanced dataset when training.\n",
    "* **We need examples from the swerving strategy in our dataset so the model learns how to turn sharply** - we took care of this in the preprocessing phase.\n",
    "\n",
    "While Keras does have some standard built-in transforms for images, they are not sufficient for our purpose. For example, when using horizontal_flip = True in the standard ImageDataGenerator, the signs of the labels are not inverted. Fortunatly, we can just extend the ImageDataGenerator class and implement our own transform logic. The code to do so is in Generator.py - it is straightforward, but too long to include in this notebook.\n",
    "\n",
    "Here, we will initialize the generator with the following parameters:\n",
    "* **Zero_Drop_Percentage: 0.9** - That is, we will randomly drop 90% of the data points with label = 0\n",
    "* **Brighten_Range: 0.4** - That is, the brighness of each image will be modified by up to 40%. To compute \"brightness\", we transform the image from RGB to HSV space, scale the 'V' coordinate up or down, and transform back to RGB space.\n",
    "* **ROI: [76,135,0,255]** - This is the x1, x2, y1, y2 rectangle that represents the area of interest for the images.\n",
    "\n",
    "> **Thought Exercise 1.1**\n",
    "Try playing around with these parameters to see if you can get better results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_generator = DriveDataGenerator(rescale=1./255., horizontal_flip=True, brighten_range=0.4)\n",
    "train_generator = data_generator.flow\\\n",
    "    (train_dataset['image'], train_dataset['previous_state'], train_dataset['label'], batch_size=batch_size, zero_drop_percentage=0.95, roi=[76,135,0,255])\n",
    "eval_generator = data_generator.flow\\\n",
    "    (eval_dataset['image'], eval_dataset['previous_state'], eval_dataset['label'], batch_size=batch_size, zero_drop_percentage=0.95, roi=[76,135,0,255])    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at a sample batch. The steering angle is represented by the red line in the image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Actual Steering Angle = [-0.28374567]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xda7af60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Actual Steering Angle = [-0.03775833]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xde72748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Actual Steering Angle = [ 0.12664133]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xdeae630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_image_with_label(img, label, prediction=None):\n",
    "    theta = label * 0.69 #Steering range for the car is +- 40 degrees -> 0.69 radians\n",
    "    line_length = 50\n",
    "    line_thickness = 3\n",
    "    label_line_color = (255, 0, 0)\n",
    "    prediction_line_color = (0, 0, 255)\n",
    "    pil_image = image.array_to_img(img, K.image_data_format(), scale=True)\n",
    "    print('Actual Steering Angle = {0}'.format(label))\n",
    "    draw_image = pil_image.copy()\n",
    "    image_draw = ImageDraw.Draw(draw_image)\n",
    "    first_point = (int(img.shape[1]/2),img.shape[0])\n",
    "    second_point = (int((img.shape[1]/2) + (line_length * math.sin(theta))), int(img.shape[0] - (line_length * math.cos(theta))))\n",
    "    image_draw.line([first_point, second_point], fill=label_line_color, width=line_thickness)\n",
    "    \n",
    "    if (prediction is not None):\n",
    "        print('Predicted Steering Angle = {0}'.format(prediction))\n",
    "        print('L1 Error: {0}'.format(abs(prediction-label)))\n",
    "        theta = prediction * 0.69\n",
    "        second_point = (int((img.shape[1]/2) + (line_length * math.sin(theta))), int(img.shape[0] - (line_length * math.cos(theta))))\n",
    "        image_draw.line([first_point, second_point], fill=prediction_line_color, width=line_thickness)\n",
    "    \n",
    "    del image_draw\n",
    "    plt.imshow(draw_image)\n",
    "    plt.show()\n",
    "\n",
    "[sample_batch_train_data, sample_batch_test_data] = next(train_generator)\n",
    "for i in range(0, 3, 1):\n",
    "    draw_image_with_label(sample_batch_train_data[0][i], sample_batch_test_data[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, let's define the network architecture. We will use a standard combination of convolutional / max pooling layers to process the images (we cannot go into the details of what each of these layers do here, but you should definitely check out the book mentioned in the readme file if you do not understand what is going on). Then, we will inject the vehicle's last known state into the dense layer as an additional feature. The layer sizes and optimization parameters were determined experimentally - try tweaking them and see what happens!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_input_shape = sample_batch_train_data[0].shape[1:]\n",
    "state_input_shape = sample_batch_train_data[1].shape[1:]\n",
    "activation = 'relu'\n",
    "\n",
    "#Create the convolutional stacks\n",
    "pic_input = Input(shape=image_input_shape)\n",
    "\n",
    "img_stack = Conv2D(16, (3, 3), name=\"convolution0\", padding='same', activation=activation)(pic_input)\n",
    "img_stack = MaxPooling2D(pool_size=(2,2))(img_stack)\n",
    "img_stack = Conv2D(32, (3, 3), activation=activation, padding='same', name='convolution1')(img_stack)\n",
    "img_stack = MaxPooling2D(pool_size=(2, 2))(img_stack)\n",
    "img_stack = Conv2D(32, (3, 3), activation=activation, padding='same', name='convolution2')(img_stack)\n",
    "img_stack = MaxPooling2D(pool_size=(2, 2))(img_stack)\n",
    "img_stack = Flatten()(img_stack)\n",
    "img_stack = Dropout(0.2)(img_stack)\n",
    "\n",
    "#Inject the state input\n",
    "state_input = Input(shape=state_input_shape)\n",
    "merged = concatenate([img_stack, state_input])\n",
    "\n",
    "# Add a few dense layers to finish the model\n",
    "merged = Dense(64, activation=activation, name='dense0')(merged)\n",
    "merged = Dropout(0.2)(merged)\n",
    "merged = Dense(10, activation=activation, name='dense2')(merged)\n",
    "merged = Dropout(0.2)(merged)\n",
    "merged = Dense(1, name='output')(merged)\n",
    "\n",
    "adam = Nadam(lr=0.0001, beta_1=0.9, beta_2=0.999, epsilon=1e-08)\n",
    "model = Model(inputs=[pic_input, state_input], outputs=merged)\n",
    "model.compile(optimizer=adam, loss='mse')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at a summary of our model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 59, 255, 3)   0                                            \n",
      "__________________________________________________________________________________________________\n",
      "convolution0 (Conv2D)           (None, 59, 255, 16)  448         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 29, 127, 16)  0           convolution0[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "convolution1 (Conv2D)           (None, 29, 127, 32)  4640        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 14, 63, 32)   0           convolution1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "convolution2 (Conv2D)           (None, 14, 63, 32)   9248        max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2D)  (None, 7, 31, 32)    0           convolution2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "flatten_1 (Flatten)             (None, 6944)         0           max_pooling2d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, 6944)         0           flatten_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "input_2 (InputLayer)            (None, 4)            0                                            \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, 6948)         0           dropout_1[0][0]                  \n",
      "                                                                 input_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense0 (Dense)                  (None, 64)           444736      concatenate_1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "dropout_2 (Dropout)             (None, 64)           0           dense0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "dense2 (Dense)                  (None, 10)           650         dropout_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dropout_3 (Dropout)             (None, 10)           0           dense2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "output (Dense)                  (None, 1)            11          dropout_3[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 459,733\n",
      "Trainable params: 459,733\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's a lot of parameters! Fortunately, we have our data augmentation strategies, so the network has a chance of converging. Try adding / removing layers or changing their widths to see what effect it has on the number of trainable parameters in the network.\n",
    "\n",
    "One of the nice features of Keras is the ability to declare callbacks. These functions get executed after each epoch of training. We will define a few callbacks:\n",
    "\n",
    "* **ReduceLrOnPlateau** - If the model is near a minimum and the learning rate is too high, then the model will circle around that minimum without ever reaching it. This callback will allow us to reduce the learning rate when the validation loss stops improving, allowing us to reach the optimal point.\n",
    "* **CsvLogger** - This lets us log the output of the model after each epoch, which will allow us to track the progress without needing to use the console.\n",
    "* **ModelCheckpoint** - Generally, we will want to use the model that has the lowest loss on the validation set. This callback will save the model each time the validation loss improves.\n",
    "* **EarlyStopping** - We will want to stop training when the validation loss stops improving. Otherwise, we risk overfitting. This monitor will detect when the validation loss stops improving, and will stop the training process when that occurs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "plateau_callback = ReduceLROnPlateau(monitor='val_loss', factor=0.5, patience=3, min_lr=0.0001, verbose=1)\n",
    "checkpoint_filepath = os.path.join(MODEL_OUTPUT_DIR, 'models', '{0}_model.{1}-{2}.h5'.format('model', '{epoch:02d}', '{val_loss:.7f}'))\n",
    "checkAndCreateDir(checkpoint_filepath)\n",
    "checkpoint_callback = ModelCheckpoint(checkpoint_filepath, save_best_only=True, verbose=1)\n",
    "csv_callback = CSVLogger(os.path.join(MODEL_OUTPUT_DIR, 'training_log.csv'))\n",
    "early_stopping_callback = EarlyStopping(monitor='val_loss', patience=10, verbose=1)\n",
    "callbacks=[plateau_callback, csv_callback, checkpoint_callback, early_stopping_callback, TQDMNotebookCallback()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's time to train the model! With the default setup, this model takes ~45 min to train on an NVidia GTX970 GPU. Note: sometimes the model will get stuck with a constant validation loss for up to 7 epochs. If left to run, the model should terminate with a validation loss of approximately .0003."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "history = model.fit_generator(train_generator, steps_per_epoch=num_train_examples//batch_size, epochs=500, callbacks=callbacks,\\\n",
    "                   validation_data=eval_generator, validation_steps=num_eval_examples//batch_size, verbose=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's do a quick sanity check. We'll load a few training images and compare the labels and the predictions. These should be very close in value if our model has learned properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Actual Steering Angle = [-0.035522]\n",
      "Predicted Steering Angle = [-0.0003692]\n",
      "L1 Error: [ 0.0351528]\n"
     ]
    },
    {
     "data": {
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7j/mXX3kr9E3TY6xL7dZKkGeSJ1chqDEZg0NgY6RVDBNVkbFtOrQO9wyjYRhHbPSIbh6v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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29d3c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Actual Steering Angle = [ 0.12993667]\n",
      "Predicted Steering Angle = [-0.0003692]\n",
      "L1 Error: [ 0.13030587]\n"
     ]
    },
    {
     "data": {
      "image/png": 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qwLpt/52UqqioQn5HJP77JuQPBpGkKAvKwBmv8yE7+7c4LjbU4TMSh5SSZ+97\nCHDvcB/rBFns12vWHzKfL3Ah3jfLDdZ5Yw/QywfIQUKtDbMA7cTSQKRY4xXlRTlnvdzQhPK6NpbI\nbMx+7tdmU24oNhvmK2802iiilg5j/TNcmJrG9VAq6nJqx48fY0yLCHNTrlcUF5ccTHxuZTQZ0O8P\n6G8L6+IeVVmSDkKtgYrYFCU7eU5a+N9I44Q0SbqEr7WWqjJE0Ssj/KMPv89OKM5bVjXztmIUkut7\nB4csplOcabrka3nxEtdUVBt/DW0c/Z0xUdAH24LFLyI/W5ZLFFOFIom2tlSbJbNZ6NNSFOxlKf/z\nw8AZ7SVsRhkLlSD7fsG300uu3i+58U3fE6U2llilxAEzc1aw+vQR6R2P08udHZa//x4uWPl0/wBT\nlKjDHeIm4JqzKXpVIrYYV7mhlRHL4IWOv/nLyL0RNiSd1qdnuMtzZmeeM67XFUrC8uGHZEdeyW8+\n/QDZ61EEQxLnPZp8h+Yjz2oZf+WbvsdU6Cmx/ORHtOsF+T2vxK5+77vEk31mH3hFqpREJRnNk2ek\ngQet25xotqB87KMVmSQQ667xUH1xgrjzBm4d+lpYj/vmR76fSbVc4uoalSRdPw2tYlSSkoWeM2lv\nyPx7/zduW2yTxKiDu5iQ1Iv6B+j1s1cNoIzvlWMc1M98EnP3/pfRddX1rekvp5Q7B1Snvr+Oq0tc\nWQIex8/imFtv/yJJ4EDXeUJb1ciQdDo+WZEORgz27rAJPTesaRns3UZZP9/DvSOqzZo8sHcaIiI9\ngPDatQ3Z7o1Xjc0+J73D+3/ofwDt4hwdSeq+98zSJCdJXvWWGo6/QSTlTzQNc876RkvbwraqpKlf\nFYeBx59NaMKU5TlCSZIoMHy6lk/Bk3NeleuAwTvnqMo1xWZFsTV4WmMdbKvWZJKTDneowvpV65Jq\ns+q47asoZrx7iAzX3Lv9Fuu64o37b7MIxV9NXXH8g3+ECuMwThAnKauggJabDYiIflCEg37CfLmg\nFP43p/OC/u4Be0cTetsGX1HK+fqMWUhILs7OkVIyGHqH487uPqPhLlUwhish2TQtTeLnsmpa6s2a\nJOTLdvpjNmXD5eKcxZnP+WAtmbTI1iv4VLdkO2P27nr90B/vkKcxInjPTVmSDoekwelsjKM3GlKU\nJUnQIVq30FQ0QcFjDb28hwpKt7XQNppHH3umjVmvSfM+L4KmHfYGlFVFWVXYYHhE7ZsKRmGN53kP\nZ0xXIRzwFt7iAAAgAElEQVTFn2uU9sfINYZ+LddyLdfycyI/Uw+91ZqrS5/BL4s10/MzFlMPOxRF\nwacYyjqENtkOMkkpXhzT/4WvAtAb9dk8fk5hvGWzqxo16HVtZ61oGCxW7IdQ+snTZ8idXWwI05r5\nDDUcoau2owwJKYiThGrmP1MJQZLn7P8Z3wk43h2BSkhCGFw1Bet1iQ3sh/6d2xRPX5DsCDZnnv1h\nYolLc0SwsPV8jn7yY8Se9wyKs+eIJKd85Cta6+kFwhrmv+upftGgR31+0llscXSHeGfXh+LBs6pP\nX2CPn6PDfURS0hYFafBwhFQUTz9j913PitGtxS4uIfQNSV97QPHJe0hraEK+IMoksq4xgfq4Wk7J\n3nib8qPv+fd7I6L+mDpg7lF/jDGW0DqHSAlMq4mapqPanT9/xBu/8CvYLRtEKJJGdxWZ089+RD4a\nsxNw5iwfUJVlh3cn+QAZpTRhLvPBLuMbr+GgKz1fXzyhrsqOSprnPYajCW0oVc+SFLF/t+uVI6Vg\ns1zQBA7z52XLoPqD8vov/4v4M122bZUDGyZ4+ZGUPgINeOd8eoGSkjjx/UUgMLcEJCGvYQChJCpg\nuAiBc3T1DFJGCPWqJW1bNxiru9C8LNbotqZu6i4sN0JR1RU2+GqCDfd/+deoA311d/eI+clT5gEC\nS/tjNptVV73qmhIZJSRpRhs44R/+1t8nwlGH9g1H99+g0ZomRKBp1iPOepSBM358NaOpGkzt58Kq\niLYuUXWOCJXKpxdXrKoSmfr1uLOzR6Ri4uBiDvpj9scTlqEGZVXX5IMBImDV42GPO/e/xDqUy19d\nLDCtgbrFBly+nF+xKgv6uf+NB1/9GoPBkK7RdZxSGwthL6s4IVKKKFAUa71hdjWjWK9ot9TR5ZLh\nICcL0KZIe9SNpq3DvqwKVqt1V80rR31aKYlDjmNZrDCNRuJbiANkgxyjPeUUQLcaC4RLstl2j/wC\n8rPF0B2swkbdrBZcnr9kE0KqvYMj3qorXgu4XT2f88Nhn8mbd3wrXTwWHX3lLYqwadRuQl2uaeah\nXcDDh4zSlA8+8vQqMdmlnc5wYbEKHPrigmjQJwk0JOlADka4xo+rf/cOsXC40OCnml4xvHmbIhQW\nVMsV0c4Ogy95fHz13nsMf/Fb9A4nuDKEwtkIYWqql954VZuCRIJ96pOkjWmQ2ZDdb/keE9nsAn36\njOXaF+xEeUpTlhD6RTTnL1BJgmxrbGhDq3WNmc2J971iFGmOubjqyt9jIXA4lg9DGwQV0b/3FiYU\noLSbNaLX9waiW0gtKlNsnni4JBpOUHGEDfRKXa4pL0/I73hoqL54iVMCQqm0dh71E2mOkltFJFiu\nF91r6xy7o0lHDVNxysG9d+gHOKSczelNRpieD9+TbExbLbsSe+MUutU0zYxA00W3hnq1hAA3Fe2K\narkkDUU+RZyRZD127/m6ACMcg9GYIrz/ebnx+jt/6H/gceckirumY4vVjChOqDahXLttSdJelxOy\n1kCU4CpDFRS0UgnGaOJgSKRSxCp5lWM2LUmWo7r+2QJjTNdkzOiW1XLGPIw7jlMQvi/SFmJpNyv6\neZ8o2KpVus96PqcKycN6XVCvF7SBztpXilg41iHJXxVrShHx/NlnPP3x7wMwvnWHs88+JA5cdhXF\n6LJgHPIek/0bWBlxFuivdeVo1t4BAMhHI1TaY1MZFqHvj1AC7SyDAJcaFaFUSh7gjsIplo1jE9ZW\nqzVlYxCBRL7nItaXV7TbJmMffUikNPOT55Qhd9LWJYc3bvHWV33uSkQJ8aDfUZCrsqRtmq7xnkxS\n4iiCkKBvjabRLWWjO8g1y/u+nmVbmJXnOFV38+lMQn+yg4y3BVMFptHo0OLEtRYVx0gVUVVb6qjB\n8aqfjhIS6ga9CUSBf4pT5X7GHnrLy5e+C1lVrlktVmzRxPlyye989GHnCZe3b9EuV1TA5qNPABi/\n+zYYgwtKKd07pLk8JRr6zb9wjtnJWVeJJ2dTnG67iXLSH5xgygobeLlWa9rzSwaTUKm4mjP8lV8h\nzsPUpLuUmxVx8Hjyo5uoyRATJjvqD8BpmuUG8Tnvrnj+lPAMcU2NHI+ol37zJ0lMFJW0Vz7bvvjg\nPWhK7JavXJbIfk4dioiEElQvnxD1egzueeaGnl0ipleUj72RyO7cR6mk6yfdhgMEbPBgpJSYsqR8\n9kkY9w66rhGjMTJ4thJH/413iPohSYqg/eAHiCx4kON9CP1cwPOgddN2XSSVEeAMrm2It73eh2N2\nd3a7ro+Riig3S/ojn/zujfd90Ubk5390NCTtD5DhgAirLS/e/y5t6+c7642Yv3xIvH/Y9a021cYf\neBAST7qq/IEeYQymqTBK0QYfXSZ90BqV/GH2wCr00/mD8uzRx9iq6hKWUZxgjekOOkiShGo9o2le\nsVyEkPR3jrq+KkIpX3m6baQVxag4IlLbgyP6CHxPbYCqrFgvZxShArbRDQ6IgqHXzkFVIlXcrfE4\nSZnPLrk88/usbhrqq7MOjR/tHnL7y1/HTLYdG1tmsyt/mAfw4tkTBmkKWc4qsG/qy1OUg527bwBQ\nVjVRnL3Ca1UcerkHY1Y1GJkShQpZkcTUTUGv16NsQ0+T2h/isAmGWpmYKmrZVD4q6Kd9njx/hAqY\nez9JaJqKLHRCfLpc0NaaKqzdrKkwumKAZnDoDc3ha28w6PepA/OoWM5pcYht0tn4giYrtuwsjWtf\nedtFWaGNIYoSXPhMksSoRKFbG57REqTtks7+4B6BDZF0gqJJJAGCp8LhKo2SljiwtKgtTusuidxW\nNSKNGUmv1yIcj/lico2hX8u1XMu1/JzIz9RDN8ZwFjigdbHxx34Fb2V6NaWSgouQPXYfPSTZ91Vx\nVcDN2u/+gPz11zh44ClB5dkZ2dFB14t48I1vsHnvQ/p3PZOjXK1Z/vBHXRn04MsPqJ88x1WVx5Px\n/WWctZShihQB0cUFPPd0wChPUYsV+sBTCNVozPJHH3a42+jLD2inU2S/R3nhfzMejXBN49uS4q12\neTUjCnigNQarNVGowJTSUVU1KlTW6br1lMJgwVUSkx/eIrtxm+LYj0v2e9w82OP0hX9dPfmU0eSA\nspqHyXYMv/Iu9UU4JbB1lMdPutYAejpHpgmyrbpj1/I8Z3PyjOzAY/23kpyDX/kLvH8SoKB6g4tT\nXIBDbu/v8bJYdNxsffbUt4yNY77y7e/45+iEp9+Fjpeqt8Oov9fh3/e/dguZJK8YJ8agG41ebyEW\nS5Yk9EO7YqUiYilpLk46eAkliaK0m+8ozcBZRvd8qG3KFa6p0OGkJSkVcZrR6j/sz5xf+s985Q/8\nvy42OO2PMANomwbndMdQAZBJhN52icwGDPaOSHv97gjELM09jr6FVFTkT2DaMpPKDVenL5iGrpAy\nydFa04RwvjeeIIzp6ILLusGQYKqG9bGPvBZVTS/vMR4FCKtY8eaD77AtHhDOsV5NqQKskKQ5zjjy\ngff6d4c7zFYLXnz4PWy47s7RTUbDUQdptXVBkuaeWQXMz08QeY/zE7+3q7JFSM166uemET3qpsHU\nJb2B99qXqw15lDArt6cLSQ7Gu8wufIQ0S1OOdMO91z1FtnGayXhCNPZr79lnDzFxhA5VtYnVjId9\ntNGsonA60HrF5WrR0QNVHKGMJlceLlHZgCyDassZr2uqusGGlgeRlKRJSiQk+nMsF9E61kVo4b23\nj0oj1rWPKAd5j0Zrth1vN3WLnl4w2laaCktZGSS2y1uYukI3dQf99PoDD4OGvEgyHvBF5Weq0K21\n3aC1EV55BlwijmO+cniTTcDhVsslq8cvuBz0yF/z/O7mak5daqqAVTOeYF1MEm3xqorotdew2zNE\noxYVqa44wa4KhBL033qDIihCYZ1v/i+2JP+G1Q/eQwZKoRKC/u4ei0e/A/iilP6dO6S3PM+6bQzW\nOFyxwW1pXpcXSClQoeQ46eX0srQrPBIS6rKhaPw1syxD7gqS2IfBRb2kmi+QATpyCDbnx1TnJ6S3\n/FxEy0tOhgfUrf9Mf2eXfLxLGx5+tLzi9Uzx8vWgmtIMu5ix/rHvixONRzitKS6vSMMma6oaUZ3z\n7le+4ced7yDjmDfCYpzeuoNrW5rTJ/4ZxjEHu4cd7vnGL//7/Oh3/k+Es4yPwjjVABFH2MABlzLC\nGd31rWltg6gaiqBsdTEnG+ygBuEoONOQxBkm9DtZ1aZrJDW+6SGApD9CYF/RFGdn7L/+dZbnXjFG\nSUTv8EGXYCyWC2prIfrD2KTeegd/QNq2RTqDDbxbTw911KUfl9XWn+kaKGavv/UWg8kuWd7rchTG\nOZI064p+BP5syTaUt1+ePIOkjwiJwstHP2by2gOGW8xdgIzjroVAXZY0ZYOrpgwCPz7XFhlJ8nAE\noIpTlJKUIZF6cX7MajEjC0VOGkM8GLAJMMO8PMWYlt17b3bh+2Y9pyoL0lDUZkREZSy9bTI3iTn+\n7GP6fX/NOOkRxYKT50/8fM9aesMRdZGSO+8YJauCqrkiDfNtcSxn5x1nf311ydvf+XUuguOkVcLh\nzoRemIsvDSa0UvD9H/o2zclgiOz1GDcFhEZkSey4WNWd4Rns7HI2X7EIzlu/PwAJo9DDvr+7y3A4\n6lp0LFcr6rpGWvx6AXCOWAnWF+Fs075vMzEJ7XJbbSnqllk4yCdGI7RmE3D79XKNspaqbbEh72Hw\nLQbUNlflBEJG2AAty+mMLyo/Yw/dsgn9TS6nl+i2Yhg6Ep6fnrJ54y721FdLLUc5utHkB4fk+6EZ\n/40Dz8kMHoq9muP2MmobvHrdYLHYQNtc/PBH2KLpGC3l6QnJ0U3c7h5ZwC2Lzx6T37zRVYLa0xNk\nrEjC4tTLJTQF3dm1TpMeHXYHyQpXo68uWHx8RRoOxZC9PrIqu4Y+rtWoNO3GcXTjNr/5r/8H/A//\n4P/w43r0CDG7oBcSRPNPT/yiCtewZYVtWoQSiGOPpo339qmTFDf2RqAq1+wd3oNn3pt2meSj93+E\nCu9nN27gehPSG55NUr18QpTmxOMJOmDRcaRIB0M+et9vkjff/lNESUQRek6kyxm9yW7nGWfjEV97\n919mvfIb6Oabb7N3+z7FZt2dsSiFwlRl16hpevIJkYppghc02fHRVDryGz3fuYXDEgUMXTcNlRUM\nX/PFZHcPbuOkpJqfMtoLCWGpaDZrFic+n3DjS7+IkJIbb3h2VDm/ZF1WXS8fZw3rzQb9EwdNe/mL\nf+Xf/YnX/8vf+q8BMOcvSbKsy9+YtkIphQ695B0SGacc3fYJY5VmFKuFPwc2KPTV7BIhFdWlj8zU\naBdTV6Sh2OtquUalmpOn3tvGtESR8iwWwBUGqVRX4drPYpxpUGrEOnS83D08oj/a6ZJ4y8XKK+Tg\nhW7KNclgRB3yNbPzS5LhABVYGIPhiETF6LbserNsyoaUGJeEqk3rzw2dLr2Xaq3FZn2adWgapmLO\nXp5ydfw03IZhk/dJ8h7Tl/5/cRzhnOtOKGvbmrrYYEIxzaCfclEW1IRK0ttvcrB7yGQndDAtxszm\nU3a3PZc2K87rmhtpzL0Hv+DXjrHc1g3LMM7eYMwdBEVY78vNGmshy7zCyHpD1lXRVY7Go12Usb46\nOkQ0vSyhWG+6PNNH73/M7S8/YLU9h3Rd0pZV16OmchAJRRWYN7f2JvTTjMV60/WbXyxX1JVmHZwz\nbRzt5gK5PXRk8M+ph66N5mXwjLWuGAz6FAFOiaKU1cPHpDd8Rab57DG73/4lyvUGRyDY52OiRL4q\nFJpMKNYzTIAMssmYLIPVh6GJ0M0j2rNTdLiGOrpNfLiL3ZSYsPjiRHoPMizw6PAQ6QwueDh2vaEp\naw5/4y8CUJ+8wG1WjL/qT3Nxp5e0iyUqjTolFtcVcZpy5yhQ81Yr7t5/k//wP/mv/L21NU1ZEH/o\nC4dWbUMURfSGobGWM8g46bLbKkuhbkiShJ1gaBIp2KXh06Bghu98g8RGbEPrtmroP3hAL0BF0dEh\n9aZAh8Tg6PUvs374EUZr4mBo3vnWn6Olh155hVMursjTjP3AZnjnl77DaDxhEhJq86sLonzCcO0N\n7nq1QlcV6/k55cYrmFv33ma+WZEFL2h883VklCK2He2sA+kVInjKVrU8Yb5t0Ssl+XCX3V1v7GQa\nsb44wRnLahtu5310W5MEo3Dy4jHtekq79NHe+N7XUHHcJa6apiTqDzH1H3+0lw4QoIpTyvmMLW1R\nAC5JcKHbooxjxoe3qYLxOy0/wzQlx08/fnXCEMKTUYKHXj17TLtZ0gte/ez4MfvvfJP9Qw95GaO5\nOntOL7BLsv6YZO8WV6FNbVnVLKaXPrke2De98S7V+WmnKC2eVpiE9Tx7XlGt1phQoBblOViLkIEh\ntFnRRjHLTYEOja/iYUZVlciQ9Ky0Pwpue6zder3GaNMxPaJYsl7MqbdQhjbEeZ/l9BL1ucjXSbrm\ncVhfFLc9qjAfHXFxdo7L/Rh6/XPeunWH6ZmP5J5OT7l4+ZLXd/zc7Ny7z3jnkKpYcXDoo2dExNnl\nJckgRM5aUxvjj5EEzhYLytZ0EepQO4aDEXvbhH0WY41mvlh2Fe7rzYraGupgMOcnJ7goIQ7VvsYf\npUQRIo1RnjKcjBiMvONijaZuNOlAEnwasnzAsl6j4kAf1gYHNEGhX81DG+gvINdJ0Wu5lmu5lp8T\n+WM9dCHEXeBvA0d49+RvOuf+OyHELvA/AfeBJ8C/5pz7I8Eeawz5IFjc3i4Pe2nXGKp8Maf34D5l\nKAKS/T75pIdMU8J5rJiq4OwfP2T04D4A7WLlE5KhaEW+/TbFyZQ4eCO6XmHdtuMyNMcv6N27hV5d\nQoBD1M1b6NkMGXDZerUgHo663uZYw/jbf5b+QTgftNfDihYZEi3zhx/6M0M3sw7Lzw4OkVVBL1j1\n/+i//G957fW3fM9goCgLPv7kPaphoHWdrYjvPyBPQo9lIcGari+LlAob/m4PHVBSovUlKnh3vZ19\nkqLtksxZnvGVN7+KCR77qUrJ9BIdKHHxnVt8ORsyn1/y63/5NwFYrVcc7d/mxhv/lv+NXsLq6ozd\nfe8x9voDqqpmsfTe3/HTT6jrFoJX1du7i4oUo/2bjEMbBEFMb7BDHGCyulwiaTm8FfDv3gBrWtoQ\n0q4WF8xfzNGhEGZweIsoVkSh57qKEvLJLirKKGeBZ76coaIUve2rslnTVBVVSFCu3vsuo3tvg94e\nXFBjREQ63OGPk2RLEdQlpmmQatuzIwNjXzXSUjFVsaIfsOwkyTFuQNlU3ZFyer1GIGnDvRVFga4q\nZoH3P9i/SZpmrBd+G7VVRdrrk3Rnn8LVcsY0HD6ul1Nmn/wIU5UkIV9z/uwzbtx/q8PQ46wHiI5e\n+ebrX6Js6q6l73KzYL2aUQVK7e7NWyzLkroqyAJenaYpcb+H2RYrWc8Ll+EQhzy/QW1055UOB0Oi\nwYjFqU+Snj/+mNtf/YZvqhZQrna5IOoP2NZNWQdZrGjm/t7OphdcPX2EDve1ePmCHeAiPPN5WdIz\nLcl+6O8vE2osojdmY7YHgDjiPKW68nv54dOnzJqK0IGXKk6oaTkIc7W7s8/h/kE3l23VYIViU1Zd\nD/uyqphPL/ng+z4XJZDs7e51vaGMaWgbgwwNAouyRGUJKgQicZyynG9otaUJ7UfKqiYWLf1wUI9r\nLXkSdYdyt8bgG2X88fJFIBcN/GfOue8LIYbA94QQfw/494C/75z7b4QQfwP4G8B//kf9kBCSD4KS\n+kZdk0pQwi/26uYBvcZwOyQ8P8iHrC5XiNiwufTwSPtiSrNYMX0vFL6EypI49CZf/PbvYqWiCpBM\nNBpBlCDToNKdxazXuNW662AmAfG5gyFUnuOWc5Kh/02UJFIKHZoXtY+f4dqSepvgNJrh+JBf/82/\nxoc/8JWeWMNf/lf/U378g98GYH52zM1b9zg/86HyxckLPnvyIWrHw0v6xQvk02eUNwIbZ7JPUa9o\nQiJL7Y+QumXQ7zEIeFqSJdy88zbRE9/7psKhkpQ0MFAmR3vMG4MMi2JydU7qNLs7HpY4EBmvf+dX\nSQeTjsN8cDMlywfdQZrVxlI3NednfjnF8YjJzg47YRNNxr/KbDrrim2siqnXG39eaejR8fzhb1Nv\n5tx8y0NU4/0jojjpqgxpStqqYnke2DhWE2U5/dAMbf/uA5Je3iUr17MzFs8+IpnsMzr0jbDmLx+i\nkLQBa9Zthd4sOkhFZTnj3SOunnuMvbw6Ro5qTP1Prgr9vGwTqcJlpCNFFXpUC6np7x6QhfkeTvYw\nKqZ125qHiFgIBoNJ13ulWszDQRgBitjMEcDbf+4v+flNcpq2IQ/h+3j3gDTLu17wuq2YPv2My7OQ\n0P9/2HvTWF+3+77rs4Zn/E97OPOd7Xvtazt2ajtDkzTFTZO2hEpVB7UMCi2gRiBVokJQCkjAiyL1\nDQh4WShSJSpKBCmhKiWUNOmUJmmTtrZjp/a17/W959wz7LP3f37GNfBirWft2xL73kiVQdFZb+49\ne+//9PzXs9ZvfX/fYbchVzkvftdnkhpVV3O6fmC+CFCEdcHFcYJDpJRolSXzrqKssDjys3BfNocj\nEs/q5CzoNgC0xgjFxZOHcR6UGO+Sm2JelgyQhHBPNmuK3VOKWDy8+MlPU1QlKtOYKQP0ZIX1PnDo\nCb2WrNC8/eUvhfdx3NN2XSpqsqrl//zLP0EWNxHvHN//Q7+bB0+iB9C+5czco+tajhH2Oju/yfG4\nZx3vdVEW3Khn7KPISo8js6Lg1bsBDslVxsOLJ+yi4EcLSZEVfGP9BGmm+drx9Te+mubacx/9CIO3\ndNGXpTkeMaMhiyrvXGcMXctuCmzROa2x7HYHmrhxn6+WeJlhmmj4JSWbtmWM81e+Ry38fuN9F3Tv\n/UPgYfz/vRDiy8BzwO8DPhf/7C8AP8f7LOjGjMy/FBo+X/r0J7nRdVzFrcuvj2xvnHERbVczQsOk\n+dU3KcpofAN0Ty/QUTDSOYfMM4oXo8uhBWVHitdeB0B0ISVlbEOlIBEMj56SzSqKIsbaPXyAlAoR\nKxY59NhjG7rXQF4WtP/wl1l8MhhW6dMlrEdsrCRm1nF7NeOzv/UH+UM/9m8A8PDNr7HbXyXhQD5b\n8nd/5q8mocZ3/+DvYvH8c/zSJOF+8DZqt+NEhIm0ZmAYDHmMwRv6liLLMRY2ceJ8eDGnPj/lxZPv\nBsCNPVYXSaH2Qi3p8Lx4Ghbf+Usf4eriHY6bcC3mJzcpior+sKOLST9bZ5jPVjz34cCMmZ0tWCxm\nKb395p0XePcbb9DHCd8e9nzl8z/PPLJLLh7fZ9zv0FnBSx8LyVTKDxRaMYssAC1Cys76aWiOmfbA\n4sa9hCs3+zUf+s7fRj4FT5uRsTsmbHX99pc5XDzg1ulNTLSJqE5uIp1BbcPNbfMVjYfnvyPYN/RD\ni6hLxqiytaZHbh6De/8kmKmStcaSlwVZFYM4vOTs7ss0sUF80bbMKkkdq71DswHv6ceWfEqiKRcU\n5YzDgzB3vNa8/OFPkMXTocSTe4kW4TXGoaO1Y2LFeO954cYNbsSQ9FyXCK1QWZE2yL7v2DcHbHzM\n6dk54zDQx+rZO8f66oKv/PIvAPDiZ7+X5XKRmGBFUYJUtGZMzcNxGJitVglHNsOIFaSTb6lzKh3C\noQG+/o3HXDWHZBExXjwir2a88OGPcnojbNTb3Y5ytqCLLJZDe2Df9okN0h0PdMNAFq+vKkr6/YE+\n0llX5zf4/N//Rfp4ku6PR05u3OL01u1kRVFWc2bLOSo22JvdnqKuuXkSTmaj9Wy2G77xKIiwnJe0\nTUM3hmt1bBswjrHrE1WUzQGbF5hofdv0jtENdLHxOhyPSCVYRLuBqqpohj6F3Tg6jvsG4QwqNmNb\nCzpz2GidcNgfGb1AxCrf/jomct9s/IaaokKIl4FPA78I3I6LPcAjAiTz6z3mx4EfB5KE/9l4Np6N\nZ+PZ+Oc/PvCCLoSYA/8r8Ce997vJoxnAe+/FZLLwzwzv/Z8D/hxAnmd+vY1y68cP6QoNUZiRzWaM\n9x9QR855X/T0T7f4dqCNApD+/oMQ+hyrEQm41nD81cBqKaqM+Xd9Bhnhk+2X38AJkQQnxfP36O4/\nwGQZOoVRS4QE20SDHiHIZhUm0oykc/heMMZjnDCG8skVL8Zj2h/7T/8UH//4J/nqP/k1dDwand55\nnt3hSB4xyPa44Xt/6PegRHjNsqrpmx33vh6Ol7Mqp7cVOuLfz92+iz1rksz82PR8/Af+RYQ36Fj1\nj8c1u6/8Cm18zn3TUgrPv/5v/2kArOn4wt/8Kzx8FGiOwg6I+ZIhVkAnixU/95P/HT/0h/8EswjD\nVFWOEiqIHIDdxcjDr3+eR/ffAuBT3/+jNNtLNvHoXRYFpc7ZXwW2yf5qg+0aXv3UR1nH1x2HDoXg\n4s3wWeubd0EqfIR1inrB4eoxQ7y+t158hW5/ge1Cldo1h/Cakfte5DM+9SP/KqPpqJfn8bMG0coU\neeaMYRhHuhgSnZFxfHzB6b2PhN/feoXj07cZuvev0MdYZXaHHWJ5znnUAVTVgmbs2UWPH9MdyYXi\nEEMK+r6l71uyvCSP/ZqsrPHOcxpZQ/L8NsZ7bLRnsMbErM3IpFEK4cATrpXHB0vd+DkHZ5BW4LnO\nEM2znPnilDxyrx8/eZfRGLYx2vGLf+OnaZpjComWX/4Ct199HRHFTrPViqeXTxi6FmKAhXcWczgm\nHF5ZQ2U6ssi2sfY2TXNkGT3u79x9gWb3lMNleMB6fUVzecE/fvSQuo6+4K+9jnn8CCJ06aVGCcnz\n3xHoqW/88i8jRsNptOQ9HhuklAl3fvroMX3/DuVENzaWzXrN/bffTCEZ5XzJ8satyWmBV157HWsM\n+020F1iucM6zjqZjh+0e7ICfgiV6g5KStjvy+H6Y4/3lJVoXiRUnTM8s10nHYqXHKUUToaXDboc1\nnsvq9wAAACAASURBVDH+2znLrA7h15N+42qzZbQq9Y32+zXjeN3749eh136z8YEWdCFERljM/6L3\n/ifjjx8LIe567x8KIe4CT973eYCT6G1+x4JZH3gzVu35jTmHQ0f3KNCSsps3ObzzDmpWY6ZU+XmN\nO+zT8VAWGW406HiEUnXF/h99PnmLCCR+7Jl9KkAI2vSIGydk8wWLD4emnH38lO0Xv5h4o2q2IC8y\niE0irOPu+SnbLwaTq9dfeZk//l/+eT70oaBg00pircc7x9/4a385PMZYnnv5I5h4nPzYd3w3ucoZ\n4iR4ennBen2JiyKr1WJFqzOWETdWXHBoPDaGAXzy+34A5xqstYnq9PT+W2yuNuk5zm7e43t+54/g\nIj4rvOCVj30XD774twDYrI80F5e4GK7wa//4l9gfB7aXj9L3M/vQ6whIgcHCSu688gluR8VllmnU\n2T1OYmi0EDC7esIyNgKNMcGP21n6mOdpx4G8mqdNWCiNECI5ZI5Dj8w1RfSkbg8dQkjGCAMJoahX\n95hFvvrpyZI8U3SNp0neOAVOZNjJIAlJtThhtooK1r6HOy8xgQTWGeSr3/GBjrL1eaDAZfMT3NjT\nRMhrc/UEqbOkcJXOsj1sktGWsyNCSZwxdD5sCn33AM81VIEQZEWGigu+UBl2HDB2MvPSCElSEIPD\neZ8eL4TG48mqWRKlWDvgpWIX6ZZt2/ALf+2naPbRQ2U0zE5OeO2z3x/ed1UzIJPXS3doGZ1CqCp5\n2JuhZWj2LCN04ddP2Q8dT5/ERe6dhwFKuxWLNe+DQChi6LNqRl3N6PqeTaQMDv2AQAeaH4AXqEKn\njebV7/0+hr6jibkDu/vvYIxLjW9hLeMw0MTPKYRAac2426PiZtbFjUxHHL48P8WMji76MJ2f3+Ds\n9JQhriePnj7i1tkZsY7iaEfeeecR3hMSl4D+2JP5jmFqbO92jF3PEAsUVMmN8xNsTPvYt3vmiwpp\npoBygdSSQ9snL31rLe1+SxPhpH4c0YsFWVzIJ3fNDzI+CMtFAH8e+LL3/r96z6/+d+CPAn82/ven\n3u+5qqrk+Rg+4XHMlgvmy7ADF2bgRWF5swg7eHO1Q85qZF1j340hxD6YIWVRXNA/3VDMS4g8dHMM\nfG7XRSZHVuCEnxTLGCsQo6N+6WX6yIfv33ontNinxeC4p86WELmpeaY5Oz3hD/5r/yYAX/rlv8es\nrtnGi/+VX/l7PHl4nw997NP8jt/9+wEoyxlPHr3DPoZ3XDx9TD9ansTXPOyesLt4wGnkVm+2a+p6\nSTeJFOsVL7/yUbJZlDl/9Us4Zzg7v8k+VkVPnzzm/PkPczNWjDjH5vFjHr4RTiuXb381BE5MEQlK\ns1wsEq7pnaXvL/nyL/xffOaH/1B4X4cdeZYhxWRAlTH2JlVmzjqyPEvVnBCC1a3nUXL6+yKaS1nK\niAtjHcYMjPFvxn5AFzlMTbwiDwZMcW0VUiKkwMYNYGwbrOmDEhPAlAzOMnZ7dpsYECBVYAIlg6qK\nRm6Yls6yqlFapUXPOxcSodT71zOvfvpzAOw3FwzdAV2Gjee4u6Ldb9LntOOAUjppItrDmm4csWZM\nrBbrA0d5YiYJIdhv95gxfKfDEGLxVFxIvRAU9Ywsjy6eWIQjmX1lGag8mKVZOVlIC7wz6Ljzf/5v\n/SyDcYjYsMxLwevf9zl0LKwO3Yg3hjae3LxSVFJzuX5KvQyN1cx5zhYrxv0UluK4ulyz30f1r9bc\n+dAr5NGeYd82bL0K3zNQKsnmwX0OfUcZtRar+Slt2yDid1RkCiEEi6nirnK8W2Ejp/y51z9OPw74\nqK68evgub/2Dv88YiyRjLMNwnSIEgcePUGSxOn7nq2/Qd21wqQTa45bLd3O6+P0c11c82G7JIrY9\ndgPDdkPX9GnzH44NUkvqeG+e37pLqVUKW5F5Rj/0SdtR5Tn0XbJR2DQ9rpjjkai4yUoZ7EemjXtZ\nVXTGIieXXz74+CAV+g8APwZ8QQjxj+LP/mPCQv4TQoh/C/gG8Id/A6/7bDwbz8az8Wz8cx4fhOXy\nd7iOBf5nx+/8jbzYe0F2Bex3e+rIVfXes9Y5Qofj0OqTn2S4e8rhS2+gJvvWUeKFpr+KcIgIlrgq\nlnf1S68jhp4xYr7j0IOzzKJi02GpPvIaQz8wxKOztYYi18yiIm0QgvNZze/7sT8OwGw+50u/9LdY\nrQKTwxnDz/yVn+BH/+XAaPm+H/5R/DDw+X/4K4nj/cZXf43D4cDiLEAov/RLP89zt26xilL1ej5H\nqQKrwmc3uuTi3bc5mfjeN2cYO7CNWPXucKQsct76ypcpIm48iIJ3336LTYzb0sLxQKv3hCkItFYM\nsRuvtUKWdWKTtO3A2Z2XGC3pCDqOBu89eTxaZ1mBVJJqCtoQgqbdY+ORZ7FYofMMY6O1cFmhlcI5\ni5xCi53FtB6vogqu1kil0klBCIl34diZ5oiQlFERO6sW4EzyO9msLxB2YL9vkt/22I947zGxWvNu\ng/dQRYqnHfuAr8dZLHVOXpaJG/+txpQvWa9O8M6m057gQxjvaOKJyZjAoR+jn4/VJd448nqBUzHI\nuKpwfcM6nj68cYiiTpbHToMTkgmFMH1H3/eM8Tiv8wytdQrXyIsKkWVInZFnMTRjHHnr8cNUxS8+\n/BHm7jo0WuUFAxIb+wfaO7SSqImwIBVPnjxCC4F4T1bBop5xiKeklpyT5yrufjSGpSgNWgdPb4BM\nM69nCfttesPJh044x6B0qMCF1FSzRXqfXgDepPk5yyuQgiHSBbNywbHtaOM8ODldMT87o30cA5+t\nw3uPdR7hw2O0dXgf7JTD9RzwkpTRunscKMkT33uI3uvTOmW9DVGRUuFir8T1HaOR3H4t9GOEgs5b\nXOyftW3DOJikfLZYjLXICCm6osbsNygsNmI786pivlphxTVsVjnBVcT6J9X6BxnfVun/MI48fhyg\n9qEfyHOdhAbN/ohRiuKjwe+7efQO2ck5w+ML5iq69b90j8NX3ki7iyzyQDmMN//x619BIsgnwcjT\nC7z3NNGDfXnnLu1Xv4parqiiMdbi+Q9z8c7XqGOTtPQCqTTncQHvh46bd56jiEesajbne3/772QR\nue9j39P1I9YYfuov/Y8AbNZX9OWM154LPOlhGBC6pI3c7ItHD7h6cp919Mroug6dzzlswmJwPO65\nePedJFZQWnNYXzGgeRozRIW3zGY1NnqJ5EWOMY5lbHC+8onP4o3BxwV+cXKTq0ffSDS8k/M7CJ2h\ndUYfaVrCKISQHCMFCwlaZRQRg8zLiiIvmUf/eUHwbp5cJMdxoO89Zuwp4iZgbXAhdxFTzPMM5yxZ\nhNa8t9jxuhHovQcRwpTD5/RkRZFSfcqswJuRmbyiib0VlAShU+al8R7nXNokhqEnL0RaLMb2gPOG\ncXz/6T9tkGGjUdNTIJVCO5cEVM46zm7fTZRObz277ZrD5eP3eKRbqFesIi96HAaKPKOPVMhufcE3\nLnc4eZ0kqrIMERfwoW0Y2zZBYF5phm6I8FGW3pfzPuWYSp2FLNJYbAzW0dt9EjuN40BZlgmbLquK\nWzfu4LwL4Q+AFxIvBLPoCzQCWBNcLQFdzhBCpvAJ7cEKkolYrQfWDx8hgKoM30lR1owe5hHeUErj\nfJagi107UBUl+wgFbXc7hrbFRv68GS3e2QSbZZkP+a2AHSfIZYKqokukMQil0LFfJqXECpGcPzMP\nWgrMhIcLwaHrcZB6DAKPrmrySE4YhgErBCIigvOqxIg+4d/eC/ZNyyzSsfO8oC9OkUokncmhG2it\nYTYL99msnNM7y80YPP3gwXWf6/3Gt9dt0Vo2TwNXeLGcIbynS7a1EnHzjF3kPOc94DNc03IQ4Ys5\nu3eH1WzG7h99HgjByKZrOMvCorazFjwoG55zcB6Jw16GBWr/6DFZprHrLTcjvnfjuZewQ4+2kWv9\nwmv0+0s+9unvAQJW+qv/4OdR8S4aup7Lqw3/w5/4Y+E5N1fcuHmH3/MHf4yvRbbHjeqEjzx/O1VW\nqprRdA1P334LCEkqb/yTX2V5Hhbf3oyMw8hVbAC13Yj3FjXdMHlBXa+4d/sm+yg6mc+CodJr3xl4\n6Gdn59x97qWkFDVmQAmJilVAczhy596LKSJtv7lE6IzTG7eTkVNVz9isL5O1qkLjFakiB4F1PsVx\ndV2LFBD0ZtCOIzrTUScw4eoVUmQpqMCNA870qWLUWRmEKtPi4S0g8JMYZ+w57LdpUZvNl5SLFUU1\nR0X8+vLB1zlcPaFcBPaIrmZIRGLSoGp0UafNzBsLTlB+AAy9jdeiaQ6hqo/CFukVfdOmAN88L0Ko\nReQSSy1ZnmnmJ2cc4ga5361RUlIuz+J3sme3vaSLLK7W55ycnuNiVerHgW7oac2kWna4cQxpSIDx\n4IWmyApUZItIEUKKpx5Et13TjRY37URFic4yiNW3syaYr8VNpGmb0LjWOWX0XVmvN1xuD4nPLTNN\ndXobHRdj611oSk7JV8bS9Uf6WBkPo6EoS/Zdl96XVxllrjnERa2oqhiAHVWeIsyvMYbGmK7Bji15\nLARWyyWn3/M9uH4KA2nph46333yTvp8YJke8t9f9ARmtqycWkRBUZU4dT+eLusKMhs02/H3TdThj\nMNFbBUL/xYxD8oNZlBXzxQwdUQTpHfY9/Zy2MyghqeI8cWNHYQeEyFDxdVWeMbcmRSTumwaZl0w8\nl3rSPnyA8czL5dl4Np6NZ+M3yfi2VuhSCvJY4ey3R3Su6WNllhcl6umas0hbOrx0GyMtqq6Qu1Ch\n/PZ5zcO24fMvhGOu+cabuGFkE4+TMs+RVYWMsIPcHBEOCnOdzbfMMlbzKh0582rG2Uzx3T/4R8Jj\ntOYLP/9/88aXvwCEqnXoR7725lvh9yj+l//+v2GIx0kvMl74+Gf44j/5Cj/wW4IysSw0T5485q03\nQxDv5uopzfGQdm2tJOv1mifROa6czWkPxxRBVS9nKASvfyzYgHYy42R5wp07z13TK7Ui1zl1tPFc\nrU7Iiix10/EFzplkfSuUoppdh9tK4Vk/fcL68YNUgeu84njcpdzRrKrRRRV8SwgsjbG5rrxWp6cU\nRZ6OvVJrlJR0fZ+k0kortJTIeBw3LtAavQsV+Dh0aK3S8XwYOqTKyOLpROBR+jqmDQKcghTIWPXr\nrCLL60TJVHKB1DJV5GZYY+2YZOZFXSMzTTteh1N8s9FMasd+oD0emUe756IokUJds4hciJyrI/wn\n8IxG451DRGqp0uqfgoK8LqhPb2FiRFrftRy2G/abAEtK67hRaNpIAXXGUhUF78ZTrveWfdMgtMZP\nalIpEcqmKl6WJVXuU7WX5TnjMNDF9yCEZPQ2xAcC3WGLs55iViPkdH2z4OM+8fZ7QaczuiYGuEiJ\nc54isnMcsO9ajpPvkAiffZFVtGOYO9v9gUaGHASAw/6ANWN6X2WW09seE3tdAkFRrdDxHtlttwzj\nkOImvbF4L3jh1Y8k2mfTDphhTP5HXoAZB8xhCvK+Qug8cdt3DFgzpPtwdnpOPvQRsgqvkxcFQghu\n3Ar9MOUd7XFHFfn1SMnQtrTDdYzg6ckJPs5N0w9YqejbEZ3qfoclYzM5wOKxXZvWqBuLBV/ng41v\nc8CFT9zLWzfO0YVmGxtySmvKsmC2jHj5es8rN+/yi03Py6++HP4m07x09zZvfjGIVDbO87FXX6aI\nPuLvZprs9j2GCF289pGPcffeXYZ9wKp/4Pf8Ac5ObuAdbHaBgiXykvMf/mEuHgW/kvnyjI9++vv4\n6Z/8iwDcvvsC9ekt6gh1nNx6jlfu3eHecyE16cnVFbpe8uj+G/zdn/tpINxou/2eLI/UPKkBn7ir\nrXPU9RyZTYEXktlijpTX2F6mFOsoUqkWK55//tMsFgvKZIhUczzumS+uvV2csUmMZKeghoi3jmOP\nO/hEE1N5CQSuex/dikReBegrLnyeYGTVdfHGzTS5zq5b5N7inUtYZT/2mHFAco1bZlmOkRoVseg8\nK8C7EIId354QGpWHJy2lRhcFY+wNCJ2RZ1laFKWQmNHivEWoyedjjtytqSMfvqgXYZGJpm1d02C6\nfcLQ+2YTjLnEtz6g/uLP/x18M4mPLEVepOtn+o7BjOj4feTUZFmeuPBChPfqlSCPEm4pV8E+NQrf\n8jwny8ukNxi6juXqnP52aI53xwOYkbOboRczDi22b/noefh93x7Y7XeYvuVR9JhxLqTkTBxwKUN2\n6YSRW2cQWlNM2b1NG/jvk5jGeLTW5FlJE+Xqfhgp/LUNgnGOTGt0hMGkkPTOIiIdMNc5zfHAIUId\n6AKdWZT0KYsT77BZxjzSQIexRTiNj0Eb23YbNvn4vqq6RHJtaAWQ6ZzBxQAMKRj7HoNLdsVCOay0\nVIvJ3Myi9IzquVDwveA+TG8NJvqQe2uoyiIJtzabPUorMiXf81k9OssQU0ACkmVVY2JDdX/c43zo\nNwEsTk+wUibIqxkc9axkpTN0DFhZHzrapmUVbZLHrkcRaa7A4v+viUV5nvOp7ww+K1974+uMPdx5\nPghG+mEApTm/HW7KWddSzecs5gseP4jRVh8/kOcFdz/0GgC/9bWPsn3363z6e38QgIv9gVdf/jB5\nrCxmdYWQnnfvB9+Q1z/xKVYnN+najvoqKvq6Pc3hyAsvhQX66CvObm74V34s8M5XZzeo8gITK4ft\nseV0ueRGjMIavvY1/upP/Hk2VxfkcUftzYDOFbtDwAezLA8qwKmxojLQOnXbPQKtC+ro3ZJpTZ5l\nCZ/Nsowb52c452ljxXJ19TQsen4icENRlqmScHbkeDymalsIAd4zxsp56HvQOftDcCYE6EcD+DR5\nBZGTPu3CPrAJ6intxlkyIcjixlQoxThkdF1L305hEgKdXW/kuqpQ3lPGzz6FN6i4mY3CYK1N7Acl\nJH3bJgaFUgpjDFIKxnhzW6Epz++mk4QQobGd1YFlhNzSbS/o20ng0wWzL/+tTY+cN2nB7psBpMXE\nRc6YIWx+cQEqy56yrBOXWGVZUG8KcKROKnioYkA5eI77bfqedZYxmpEyBh9kWYEde0wMQrbe0w8j\nfZxXHkGW1yA0L9wNBUdgzDi+/jTcM0IrrPEQ52/f91hvU69FCgXWJuaMKkv6fuDq6ioZojnr6Pvr\nSEUvJf0wvCc2MJi4MS16MuP0/Jzzk0As6PoW5yxaK6o4x5VSjOPIOt6H1hmwLgmiyjxDeJfmb2tH\nxixLhUGmNdaMqU9SKkmeKaRWlJGw0HYd52cnybfdIxi6Pt1DQgqwNim882qFECIVXnUuEW5EeZ3u\nga4ziBhwPX0nHpdStLKTM45XW1Rkl3U+NGL72DtYnZ8wryqcF7z5big8D4cDTmq6yKRZzSuaY8c8\namEm1ekHGc8w9Gfj2Xg2no3fJOPbWqEXRcHte+H4+Ns+98Osbj7HneeDEuzNN9/keGhRsZL7mz/7\n0wxDB87zJ/+T/wyAey+8xHr9hO/4VHQH3FzyCIuM+9LHXngRYy0+VuhKZ0gt+MLXgsPjcy+9yltf\n+TIWQRu753Xh8ark818Ilrx/4Pf/EepPfyfb2H3X3YCXGVcx169pWx69/VX+5l//3wBYr9eM48ho\nTDrWIkJVM1Xgh3aLziuW0aKgzDMypcinENiyQgmZ6FSZ0nRDTxb7Ca9/4rs5Hg80bUMXrT+zvOT0\n7AbLs+vwZGc9Yzd5bR9jBRUrduc4Nhu6eAw21tA3B6z3tJHxILMi0A3j53AuqO/yMtK60AhvUvLP\nPM+RQiTcvh0sDo9zY4JMrLGUVYGuIsfWe3RWYicaoi5RQiYLXiklpu+v0cUs0My6WAk3+z3OWcbo\npAmg85yimqF0NM6XksvLJ8xPAhQnhMTnc0y0Zra+p7t6lDD1bzastbh4PSGcerI8VE1WhO93ogO6\nQTKIAZVF10ItgoWq8ylYevpME8YbGEIyQVhmHCjLgmO8FqYfcVmW3Bjdfk+1PKGNvixmNJihoTns\nEOKaU+9xvFaF6ni3W7PbXcIY5s2uN2RFgYve8FKqAIHFKnDsLN55qsWMcsLQc02hs/QBpFYI75IN\nghkGyixjF60YVic1uenIIitmtpjhkYwOJvlj2zSM44CIc+10tgAEy6gkHcce721y6UQKnCAxsMqq\nxBhDWYfP0R4aysWMfnTJ0+dkUeCco419OqkE85Ml28gxFAC5SjbLZVlQ1BXbTVQcn56ihMSMHS5O\ntptlhbPQDpN2Y0TiGOP11Loku3UjWQXgwVlYRYdMpTSXfeDXF1Wd5oVxpExWay2L5ZwsLoaT1ckH\nGd/WBf385i1+1x8Izce//Qt/l/uHN7j7XMADT+c1d2/f4Sry1G/XBe+0PVoqZMRPv/Qrfx809PFY\ntlrdwOiCn/rLPwHAjdUJ3/M7foQuNrJWp6f84s/+NWSMlPr5n/0/kMoydCbRo+o6Z3ZykuLf/ux/\n/h/wR//Ef5S8y59//gWuri7oYgPtwVf/MQ/vv0MZKUcIhbEds+UiNQeHtkVISRmpkYemIysLxnjs\nsv9M2rzxLbnKECLKyN2AzCpefi2ENffG0HQtUojkZ746O6PIi5QF2TYNfdvRR0jFDQPg0qK3uXpC\nVtbpc7fHI7qYIY2jXMYm0Ooc6S2HGN0mbUZWQJ1He4Z6ifSGIn52GRjm6XOoQlPIjIM11IvwvnSm\nEQhExGy11igtUTb83lmD6Xt0FLaUZc04tJh4rYxxGO/SYqK0oswqqGZ0bWx2+dDwHqPsfrlcsViu\nEn/ejgZfesRkN3AsabaXyRb4m428nCU81jsXNhs7hcs6vJfBxArwuWG0hixy8m1qgGfo+Nk9YQGY\nGrzeB564ilDGMHQcDsdEIRRSU2qZPD4k4EaXPFaGbsAKzYhI1FPTNaCyBJcU1ZKFgF0Mni64YjQd\nN0T4/YM2iGcmuMQLhapyLCJtREM/IoWki59VCEXft4l73bUNXookBsurCo9IuaWXmw0gMNYnCt68\nrlnWZbq+IJEi0AoBZF4jhGC0U86mpS5Kimqi5RqM9yxjgPnt8xNGYzGjSX2MtmvZH/YsYv/LeIty\nlvOz03j9PZYg7Jm+D2E8Rex9CZmx3m7Isjw5xY7GoAvNMmL/mRSMo2GM17sbLdK7FK2XZ1n6nsN8\nCPF87aFJ2owsr5DO4yIxYDGrkMrTTeHhMdDkg4xvc1PUISPm+9nf8hkun274Sz/xPwEwcz0f/67v\n50vRp/lis8EeW+aLir/w3/4ZAOazGVmRpxvgMAYDnnkk7TsMT+//Gk0fJsGxeYqqClzEIHdNUFKu\nLy7YRdfH2XzGYrXgxZdDuO/l48f8mX//3+GVj4ZAhu3VE+698Byn56ESXsxnvPzyy0wLmTEj210e\nuarhdU9u3ALB9SlgsaAo8qRkLOuKIstTh3+0Dul8co7r+o5XP/adKfcRpzg/O+f0/CZlrNr7oQss\ni0n52XQIIcjjYtG5Q2SvxI7/cc+4Xie+MjLDjQ4vYBaFWCrLGHvLLPLjc53hvbsWtnR7tNJk5pot\nAiJVEM44tu0OJQXVhCnmGVqpJMzQWuGtw/v3BC4UOcaI9BxOSIgb1exkjlYinSLcmDN0A/3Ypoq3\n71pKlWHNVIHPURLaffRHHw06r8iin4nKS2RR4TeXfKsx9G1aHLKsCJuSnBZ4ifcufed911LOVGJt\nIQSN8xRFiY2LgcCHBnBc4KWSWCMSE6kdRqpqlnI3JaFBOQl4Tm7dwoxj6nlU+y1t21LOlskbvu9a\n9pvL1BQ9HDZorbCRZSGxCCTvxoXyZFFimgMMYa5ejjA0HnSeNhYlJYe9T1WqHYdwOkkeSTacsqb+\nzThSlGVitJV5iUBSFjIxZ6zpQRZk8TW67gBSUceKXMjg7eKJbqxKozORmrdFVqCNTAytpulx1iDx\nqRk7DOEEMMT7P88LqrpIvRfjHLnOOUZnVWMsVZmTx+st8bx49ybO+cRqk6rmeGxQsVjrh4FDe0y4\nvEUwjGM40QC77Q4DaR7l1YzdoUUIwaye+O913Dxj075rGIcBHYH6hZ7M2d5/PMPQn41n49l4Nn6T\njG9rhd61LX/vb4dYttX5GWQLPvpSwNAfP13zd/7GXycvJx/nK4wd0WVJOzmVdQOv37uNiR36YXtg\nUSzS869u3sCXNWMbXQ4fHWjaPjk6tl2Dd9Ac29DdB7p+wF3t+IYP8WSvfscn2O4OGBN9LG7fIMs1\nTTsdzx14h4zH977raJuBw3GfqEqIjLzMUwyY0hnWWrIqQhtlRZ5lSYU4HI8YY0I+J/Dxz34/qCxV\nL6vVDU5OTsG7VOlWZYWzNp0CqlKz2VwlWME4x9B3CRs9rK8o6gVFzOZc3bhF14+MpksnA2895axG\nxH2+a4+0x0NSeS7nc2azGW3Ex431SCnS40XsA0ghcX5iSCiQGhN55/Shaq+i17a1jrbvsREqMn2H\ntWOqksahw+k8ORCCoMwKUDJx17Oyou9aiol9Y0astcnDY3f5BCElKuLK+XzFMFoc39rLpe/adJKw\nziJG9U/5v3jvIVacRTXHjGPilI9mJM9yvHfUKlxzqRXOk+xaTR96L5OD4Kxe4LxHxtK3qCq89xTF\nxNpoETpjcRI+5+nNm7THjm5oU4/hsF3Te+ijp4ySmu1+SzfxtWVGpkhWCsNo6ITGZAGWOF3W0O1h\n6GAelLfOB1fM6ZREXiHkNVSh8yyoZN+TrOScSy6cWVFgnCfLNNto1yCURrmeJkJTdVlSFXnyDbd2\nJCsrZpHKJ/OMsR8wNtoCjyMISRZPnId+QHlJYwasjCeDWcFMZQmOag8NZr1N/O6yDArlqW+XKYnp\nR7qoNC+LnOPBYLxL37tW0JmBNnLG266jkDoxk8q8pOu6hETUy4xdc0z8em1azmrNfLZATyw3ZxmP\nDWPk6DvrQ7pahHEmWusHGd/WBV1nOS+/FHzETb3iH/7MT/LO24Ey33dDkE3H+6Veztle7TnsdzpU\nwwAAIABJREFUDin/8JWXX2TTWYgeB3dffB5rDH2kGWVasLtas9/Gi90emC2XrKIv9uWTC5rtDqlz\n5qtwU0gFSl37QefljOdXJ8mv+/LikubQMosUouN+z7v332HqZFX1nLwIWZ6Tz8TusEe1Gh8hk7Io\nmdV1is7rxchhf+QYsdFh6KjqGd/7fT8U3oMuEFpyehZuqFlVYYzBeoeJvitd15FJzS5a9Do/st9t\n2FzGuD1rWT96h3HyS3/uFep6Th1l504oRjugdIkg+l67DudMokI6M6C1TP7QzTGEbk/N3rwomNcz\nutan71dngac+YftCCIQQ6bNXZYWQ4j14rAj2uPHGHp3FmDE13HSeo3xDFxdvhAyLvrdJZCWFZLE6\nTfCTHUeKssbHGyHLK7pmTx4lDjhDUdX0w3XD89cbl48fU8dNuZpnoXk4RIxXa7z1CXIRQiC1SgHD\n3nuGfsB5cH6ip3qslwmKkDpsEDJGzhV5Fg3SkpcwmVbXf59l9H3LMWL/8/mKrMg5NkeyuHjee/4F\nTk7P2USr26dPHiIuc3zUXZxk57RNkzbQy80aJTXNPiy0O6mYlQtWyzP2sW9k1heIPVQxmCPTGpWV\nsYcS2xsqQ8UmvxawfvqUKsISuixRCOaLZaIIPnr4kJPVCe49/QQnVDK4QwiatmEdczc9grKsmEe6\ncLc7pBB2gEoFSnGV6dTI7sxIXtVk8X0sViuUVOjY63JYcpXh4n26OzS0bccqetYIVeAKhfKeJs7X\nft9SVTnziN3PqxI32NQzUcJxdrpKfjBmGMlyRTuRLKRmGEfa7SYVW97Dvu3Sa1RlQa5k8kEX+oMD\nKd/WBb3tOx6+HYIifu2rv0bXNJTRxGm3bbl9Z5Vwu816S9+1zGcl5yfhS+xHQzabcRq/1L5vKasZ\nL38ocMjbtuXq4pLLi6i005rlacF2MyWSrDHOo71nHydKXdc4KcmjP3TbtCgtMdFbWWYZTXNkfT90\n8J0PnN2pah3tDtVo8rJMi5LzHiUVeZxIdjzivETpWLXuNhF/nBqFJZ/5vh9Ji9jp87epqzwp7/q2\n4dGjh/HmjXiguu4lhNfUSKHp1sFPZvvkAYemo4phFMYR+EB6ClNQLFcrpPRMFoJSCdwwJMM0p3K8\nMwk79XjGYUzd+CIvGY3Dx2ak6EeqeobUjiH+bLFYpYYuXDcXp2aYlIJ5PaNXYYFpDzvMGHBYiPjs\nbIaNfPVm6FkuTujXTzDZtEnMcNanDdR5D+9RZOpqRqnkdRO075id3ubW8y/yrYbOFe30GKEo5/PE\n1x664CsyOVN6ETa06Vo551HCMA5DcvGbGsNmCHN+tlyClFgfPuuu72jbNiUpqSwnyzXFpGouMopy\nnnzdpVI469BFgYn9g8FYjHcUkZN/fuMOs9mSs13oAV08vaDxHftoFDefn+Kdo4+V1CJX5Aqu2i6Z\nVulqxaY5Ii7DfaWtxcxPuXMzFErzPKc7HtivQ4Fy7EeWy5PkRVRUNdv1FVpldHFDPLl1jyLLk6GX\nUAprDE0szrQSFHmJiwrWTOXYsWM8xFPrYoHHBz0AwdfGOtg0XTKkG6ynzLPk227syNgO6WRXFDn9\nOFDHBVwVJcuzk3RCarvgLOqkSIHZ3htMJzHxnrHOgXPXyufjgey4S6fcY3vk7Pyc5SKsL0II/H7E\nmFCAAjSHDtF3+EnjYC2qzKgjnz6xtz7AeIahPxvPxrPxbPwmGd9e+9y24f5FgAQePHhMXeX0kRt8\n9/nn6Yae/VU4+m2uNuRaMuI5xt3xxZdfYlHN2KZ4OE01KxJlqNkd2F5eMkQ8cTmr2FxdIGPmR10v\nyTNN1zTX3fFjS5bnKBW9FozheNzRxc63xyPlNTMB59BKJT/1oSM4PGbHJFNenZ5wenaaPE90kTNb\nVKyfhup5GAzVfE4V6X+vvv4pZrOak8ib9h763uBj1XQ4BtvQq3ffoYreyL6Asl4hYjWx3W95+NZX\nefQgWBgMaLJqgZwyG8cRqXL2kcOclwVlFfjvQ6yG7TjivcNNLABryHWRbGnzskALmTjPoRC+tjA9\nOT2JJy6RKhgzmsC+mTxkVPB2mY6ozo4cxwEfMd6yrqmlwLuofLQOM47Mo+qwtI6+63GyYLUMP1NS\nYRDIiNtbYxGSRHdtDnusF8kJ8fD0MVZk9PZbY5O37z5HG4/Bw+gZxjFZ12YqDzTE2N+xY09eFMkv\nfehb6iIHKVO/xnsb8NsIBV09eRK0C5NLoTVYT2IVGXNFnhWsoid76QpAJMhLWhWyLT1k8cTYtA3O\nWuYRe75xfpNHj+4ndpQUEjv2qT8zGkM7WKr4vi+udswWC2RWc4ysrIGRxXzOuAnz92gFxeaSR8cw\nl4SUZLMlPrJzTKZ5utvRx5Py3Tt3sOPIxdVVOtFU9QxkyGYFcG5ke2yuLR+qCoNDRFitsyN4z/pR\n8P/fR7iyiacZYx1aaQqtKSZWkdQ8fndPEZkzXmtklTFEq4uu7zFmxMXnKo3D9B2X0SsnUxnCw2xW\nTpGh1LMZdhwZ4+s+ePcJSnjOYl/j1o1TlBRJJV7ojOHYpZMdWrA6O+Wm0rRTDsGpoe97hoi0Hbue\n47GhjrYep6eTsvj9x7d1QbfOcXUVjrDtsWN7ueXjn/gEAOv9mqunTxnaIf19Vlfcev4udZyMZugR\nyyXH2JyZlSXCSdZPA3zSty0XF5epufj4/mOk1MziDdEoKPLgRzJJ4OuqwlifrG432x1SKhbLKRxh\nQGUycYczXyJEQikwzlHVFfWsTtLosiqDZ0bcBEYzsrnaUkYjrdlC8urrv4VZNPRZzFd4Z1lvwmZW\nlRWdHalMPHJJx2I2oyrzJLdu9kcOh13AvAne09WsRsfJq8oVp+c30bFRW82XqLxI4qWyLCmynGHo\nr/21cQHDTNxgyIqMKj6nlAo3jqlJ4z0sVsvkcyOEYrA+BI/ExUAqgVJ5ohRWVcF+fUUVvxOlc3Kl\nkr+JtToIkybOvjWY0aZmWdcHyb0uioRBYgf8eyLlvAesSTzobhjIsozjJuDIg/OI3dV1IMM3GfXy\nlGo2hRQfsJ7U9+itQ7oRF+eaA0Y7JrMu6zydsOhMJ7xaao2xNvnsGBuEWFnsNxD7F1Ox4H3YnIbY\nkHN2iP4zUaafZRR5RV2XqRmb9R1eSIrsWjR1enqDici/Wp5x89Y9Nsl7f8dxt+P+u9EzXBIk9/t9\nKh4WiyVCF5gq/PvMGG5VmjHi8ofDkeNhSzNloZqRg79uHj/Z7JjNF5QnZ9TxfVnn2Wz3tO2kzejo\n2pY2Qi5yGJFKIeKma0yw4G3itVNlzTAaRh/mzeLkBGtGrPO08Z4QWYFQdXrOcT8yX8yYl9cZrsNo\nE9Z/bAL9cIwL/shIJgRD12CGqU+n0VnGME7iMId3notNpEo6uH3rFucxVEcQuP2TB03f92RZhcx0\nCo333sMwkMf7rhpHZstlojoeuvc3kZvGB17QRSjL/gHwwHv/e4UQZ8D/DLwMvAX8Ye/9+ls9h7WW\n+2/fjx9CcHbzDu9Gx0GVa8zoU2isVJLVyQmLWY2Ou/q8nnF1cRFYDvH5NpsrHr4dAiy6pmMYx2u/\nY6VACXQ2sQhqqjJjMZsnH+bj8UjT9xCd4/IsIy+zlIxS5SVKFZiIc87KEoGnipj7YrkIIRdtSxYX\n/f7YhGzMyfBoNIyjYXUaMMff9rkf5XS1YugnX2vPrCiTOVfwC09aDzwy3Nyjoz2G00nfNfhWYuIk\nOK4vWV8+YRGNnMrZApGX6Ghg5b1ACFJzMmB8EiVVYjzoSnM8HBIeGypFRR/7CdY2AdefDJPKirKo\n8RNjomsRUqDzEhf52lIHrH/Cga2xzJenjPFU4KTHOEMbX2PsW9rDHjMpF+1Id9imJHbnAaGCgdkq\nnmikwIzDNatICdrjMVV75fKU427N4mbwCRIXD/FjR7P71rnmDskh+l73g2Vo9rSxMiurGW3bp2AJ\nJRyQJ8OvXAucHWi6Jm0ceVGCkNcpPFmBVjJ66MDq5AbOmuQlYk0w8poa30ppECCnRCldwNyR58t0\nTxSnZxgzJG+Rtu3QWZY0EEorlosli9gH2R33bGYbNlGM1zmPsZZituS4D6/bDj1KD8l3J1vM2ZJx\n41ZwPa1OR/TFE+ZRjWrkjNI4hkkR2zacnJ7RDwOPLtfxvWuatr0WL40jOqYvQTg59E2bdGvz1ZIB\ngVPTSU+A9VR12HDPTs/CSdm7ZGCHyjBjhxjDv4+HhkNzTMHSRabBWd55JzZelQ6MmCmbVilGIaiq\nEhkbk8o7fNeSx024mlfhdWINJHD0TZMYLChFWVXp3lZKsz8cabsuzWljLdvN9vqGVwJnXOqXTc3+\nDzJ+Ixj6vwt8+T3//tPAz3jvXwN+Jv772Xg2no1n49n4/2h8oApdCPE88C8B/wXw78Uf/z7gc/H/\n/wLwc8B/+K2eZxxHjhFbWp2cMpg+MRHa9Y5cCbKps1toVJ7hrKCIFclmuwnVd3zMk6dPMf2YIBaD\noF4uqOoA0Xjnk2dFeP0eJeDR4XGim+32DUjB6Y1AyaqqkAU5MT2WiyVldV09S6XQOk80un3TUWQ5\nq7Mq8W69swxDz/ryMl4/zep0yWe+518Iv/eep+sNq5iqvpotqKsKF6vUrK5BiOScGJgSPfvtmm3E\nMZUK3toTW2cYek5v3btOBpIa42AC/2bzJWVRJFdD6YNkW2udfCj2myuMNSyj57f3nq7rUpxc3494\nLyjj9+GERCqRku4dBukFApsqRp1p8ixP4IYQIeLLRNhm7Hv6vk12Dn3X4qydyE5oIalm8wSv7DZX\n3Lz7En2z5dH94Dd/87mXWZ2skud613Ycmya57MmspChrdFSK3nz5dezYs3n0Ft9qPL7/VkqVz8sK\nVZbI+L07P5LlWfI/t9aBNwm6k1mOzHLcaJh4n03bJQodhMxKLWRiAPXjQFlV1LHCHNoO8558Vq1k\n+M734ZRWVJbzmzeTR/c0JmUpQF5IHA157KWMokPrij6eNLK+RQjPvXuh2p7PFuyPR/b7PdV50Ihc\nbTZ03REXy+XDfkdeZVw28TsUmny5IPdh3rjjgWF/RbYIPQ6tM/a7HeDTvDg/O2Pom/S+2+bIxWZN\nE/tODkG9WLI6udaZFFnOMsIlfrRUp6cJ+pR4zDigZJ6k/vvNGpznUYRkN9sd1prkJtq2DblWnE4s\nF6UYhz65no7GoHTG8vwmbVTz3r1zhzLL2UY5/pNHj/FKIeM9VM+X5FWdKJzLxQLnHIcYTbjZXNEP\nFmNd8vTZ7XYhPi9eCzuONG0b4EVIP/8g44NCLv818KeAxXt+dtt7/zD+/yPg9vs9iZSKm3fCnymh\nePLoESoeZTIpuHPvFsf4hZ6cnCB1zmK1Sjjx21//BmVZEm2EKZRic9imG3e5mlPXNV3MJcR7pCBh\nZFWZo6SizDV9xOJulRXHtkuNKtO3aJWlhhtS0bbXpvdZmSOUpJoyAssM6S19119T8wjQwvI0QAKf\n/f7fxWZzRR4XxuViSZZlZBH+qMtZoPOpyf8keIY3ERYCAn3Q9CwirNAedjz5xlcpT4JMP6vmHI4t\no4/hEzfuUC9rlnFyKxlscKegA+MsUkjaoeO4DQtE1zWAoI02nllRYJ0JHuhAdVLHTStc8FlV4fFU\nkaOvxyCkKXSZBE7eWno7xGg5GEwIHZh6GGYYcc4keCRTGXVZJ2FS1/UMo6GNcHmxPGcwA6pYcPNO\n9JiJAp5p4gcb4Wt7XOst+vTs2oRMBX/qMvrof7MxW51x3Aac2I89i7NbqcFmRsOjB28z+SZ54ZBS\np0BtmWW0h0OYmxMn2Y5YN1LFTSDTCjuaJHQpyirkjJbTZqiQKqeNcAhChEyBCebJitC0FSJln+Z5\njlSSPm48Tduw3e1ZxMBslVW0fZcCRO6tXuHk/Babq1B8bHcbvHM8vXySAliGPsP7kj7CkMY5LpqO\nKc1au4ah78gmQZoziCLnah0grRuzGqdLzk5ukkeq3nHzFEswhAOwUnFyckIRm/ZtP1I4zyIurrPZ\nktFcU1FnM4UdB45xc/v6/QeorODenRus41zSWcbV4ycMESrKM8lstQpaCYJwqC5y6gifIsKGmcff\nr05OEAishy4aeOV1hXQjs0kjcuMGu+2WyyfB++nq6hKVHdKm0BnL4XhMNF3rJd1wpNkfk995lil0\nNUtQkBMihF7HMmh8jwf8+433XdCFEL8XeOK9/2UhxOd+vb/x3nsxEUr/34//ceDHIbAkJgHP7nCg\nHwaqmBh/6/m79MZwFj1T6sWCTGe8/fWvc4islts3z3HWJWXderujmJUpkLVpGuZVxflZXIwFXEuG\nAO9RUuC9R0/MA+DGzSVtf81yMXiquEtoISnKLFWIQz9wPOzpYuMq15pCC87OTtCxedu1Iy987DN8\n+JWXATg7OWW4fRcdsTDjRrwzeBf+vd5cYI3j7DxMEmMH3DBiY6PLO8fY92T/T3vvEmtJkt73/SIz\n8p3nee+te6uqe3qmySFnBpb4gKmFRBAECdjkQCatjcCFAS4EeGMY9kIL0tpo4QVtw94aoGEDgmVY\nsCEb0tYybHhnWzYoPjWa4fT01OPWfZz3yXdmhBcRGbc40z3TBJvV4+rzAYW675MZJzLii//3//7/\nMGL9ymi7f/jNP2aIcieQ1Jd7JstLhL1urQbi18wourZBRhFibHLRA/f3N3jioeMyTjOGtnWLbZyn\nTKYTVxBWXYfvh6R2cYjDkIGBzk72Qff4QtL3HX01Ys8N+IF7ja5vmM8XBLYgNOLCorC6IcKjG3q2\n1kB7Mp3jhyFTK8okwwChFEOvHhbCKDTKkCOHWUrCOOVoH/Z+UBB6RLF5cIdhQEqBF72en/zZ+B//\n4e8yK7ZcWKPv3d0NbVUwOtn7nk82ndLb00mapnhSOp2Vvu84HA+EYWSYKMBmdYfne1z6I07cEUcp\n29HsercjiiIOttjoy9A0KNmTW1UeOBR75rZRLo5D1GBYRgfrFSsb45IURQ+4sVbaLfCd1bwfmUpN\n2yL8gCeWkz87zs3Cog1HHeCiKnj14kN2drEdBoUQPgerCtnREaaZO8ldBQkxiiePjB79/c1zqqaj\nC4UzffaEJMsmKKtBs7q5QQQxrR3f2WJKlqZEloPdVbXpJLXff3l3y6PFksF+XrUDPj3HonL6/Ncf\nPidOI9cE5EuPs+WZO23vy5JwMnH1htFdq7J88F1RITzJoOHe1jGmrUEA9nYsUIqy08Rzs24RZzRN\nx9q6IvXrLYPqXU2o6Y0WvecJV+s7bAuEKBja0cjbaNL44iH5+qTxSTL0vwH8mhDi60AMTIUQ/xC4\nEUI81lpfCyEeAx9ZYdJa/y7wuwD5dPKRi/4pTnGKU5ziLx4/dEHXWv828NsANkP/u1rrf0cI8Z8B\nvwn8jv3/n/ywv9V3Hd/6xrcAUw0OPI/siYEM7tb3XD5+zIcfmAz0naePEWpgEkUkC5Nxl4eKsmke\naF8opvM5cWhuI01iZOgx2ON61w4IxIMbTtdTVCUykI6REqURnVIE9m8kSUxZN6zurG+jJ4jDwLXD\nR4GHEB6+PS51XYevfYYeksRkjD/xc3+d97/0PnOLIe72W1TX0thsuqoOCOETWzgkz3PiNKa1Sn2a\ngPK4c92qfdcyaM1xu+LO4oGDF7FYPnLZSDx/B+HHTn4glIZiWFi9mCjL0YNyLAIGYSiIWjndaul5\nJPM5crTGE77hkdtMYjLNSeLYsRqbthm1ax/e46HEk4FTEKyb1rjR2L/RtA15njsZ2r7rjaaGZRa0\nfUfTVs7vU3atgc1SAzWhFfEkY+h7pwuudIQvQwZ3ylLgacdAkb7Clz79yKxR0HcNfTvay31/LB6/\nR33cs1+ZmsXs7BylFHtLfRSeRPc9je1X8IXEk8ppEeEbfe3tesPi3MzxgQEYuLenjyybIkTgeNNK\nmdNGVVlYIU6RUjqtnO0mwPM8h0M3ZYHOZ9RV+eAQFQRMp1NWVr+/HwayOAILyeRpQjcMjuvuBYHp\nZbDPSBglDAoun3yBG9vTIFTC2Vd/ymH3+92WfVkS1WNtpUZKydUjA6dO8gmBjIisguNkfsF2v6Y4\nHGHktg8aL/DJ58axLD+74P72nrsbw1i72R/4K1/7CkKNNGaf/W5DbMd3loTc3N2ysn0rIgho25aX\nt/ecLy1vW0DbDOS5uc7lfMrZ2Zlr/c/rmrrraOz8lUCtFIHVBJLCMLe0GkitReJut+bD5wUTS7vd\nFwfDRrLjP0ly4jgkDG3GjuZYHBksDVdtdhzLkrpuXN1ucbakq2u2jbkX6YHSHsLCU8EnbxT9C/HQ\nfwf4H4QQfwf4EPjbP+wX+r6ntjjR+fmCOI0eNA+6jm/80b90k/vb3/wALwjwhWBqPQGrsqLXiqn1\n2JuEiTHBsFydODC2bqNvoRpgMknJ05HCVRJIQdMOTh+j6xWH/cpxPj3pMT87w7M+mcWxBK1cI8ah\nE6RpRG4Xaz/wGYYOP8l57yd+CoDHV4+Jg8QJEW039xTlwTUazRcX5Fn2UGiVhg878qjrYk/bdM70\noa4btFYURcnTL/8VAIam4rBbO22WKJ1S1ZXT9EiShDCMiOzxXKsBhHBQ0TD0KG00VsbCVBBFxmjD\nFuGGYSBJU6YWYkmSBBlIagunBEFI27WuaUINA7c3N/RD76h1vu+b47/9mWwyZb26cwXfdDKnaToS\nC4f0bUtVVQ7jrduBOE5YW89MPSj8/ZFAhg5MO97eMplO6S1/2Jc+aZYR26JzV+wpy6OjCyKM/Vnb\nfbyWy+7+FUp4jqYo/MA0g2XmfT8edyT5hL1thy/1gA4Cut1IRWuZZBlxmrKzMr3z5QVRGLhnoK6O\nVq7Awk1BgPCks6QDj6IoWVi6q0BwcXbBwWLqQ99QlEbnZmILe01dsd1umM1m9jp6pHwQqDoUJWEY\nkNj5H/g+u90WbcWlZCBtX4FwG3ux37NZ37vmpTCOOY8Tpv3EzhNN2z+YVdTHI/t2zdx6DNRtz+DF\ndLEmW5i/eR6G+L7v6lt13xLFGZMzA9PcXr/gm9/+wEnf+sLn8cWS1b15z5bzBan0aC2J4sl8zrFq\n2R8OrKwPbJ5PKaqKo4Wgz7IpDZLKzhPteby4fuUU/ZNsQo/Gt7x/IQRd2yKQhiaJoXU2bU9h/RKU\nVsRRwNmFuW7heQydIhgt6gZFHMa0tjCezEAmKYfjwTX5bT1JksYEVtLE8wVdUdEe7PP/Wm/OD4s/\n14Kutf7fMWwWtNYr4Jf/PL8vwAnFD9roVD86MwvSdqdJHiUk4cNE+9aHzzg7m7tdOI4D0jRxVWpf\naBazGRubjcRxShz7D8YGdcVxf6BrHwpEnpAgBDuLiUlfgBbY94uqqNipewJbrJ3NclTfktomIClD\nfCmdM1AUT/mlX/o6Wgsuzi/tdUQ0bckwZthtg68El1ZnvCyO3B32XFncsqlKEIK9xU7VMNCWpXNy\n77uGzXpDtrziYDMB1dQQZq6RaHc8UFclk9FodtD4Sjl9Gen7RifEFow2mxVxkhjXlG4s2g0Ux6Mr\n1izmc2bTCZld0IWArq6cQ5HwFZ7vucV5u9/S9S0yigjD0ek+RAbRa4uUolfaWaG2/UCaSLeZHQ57\nssnU6SA2bUvXN+7nPekTJymBH1JaAao4SdHqQZu8bWqEgDg14zc9u2S4e/ngKdr1qEHR1rZ4/hHR\ndy1d3zOxG6ZA09c1Y3mqbVu08Dh/530zb8qC+7sXCN9sROePr4hlQD5dcP/KZJ2T2dRkw/ZAs1vd\n4MWJcTYCJtMpQRiz31t8Vph7c+/H8oyqqpjbWk1VFtzf3pDPZmy35ndk4BPHgRM/m+Q5URy5vosg\n8Oj6nm4//nyA8AOHCXueR5QkVEXp3kMhPRbnF8wslvuob9luNk53pW1a8HK0xXzvVjds1yuuN2Yj\n69qe/foOrZTbWJbzcx4/fofCJl/VsUb6PtYci+VigfQEjcXYP3z5gptvfYAVLCVJUtI04fEjk+V6\nYUgUJzy+vOBgN8zjseBYN2zHzvJngmmeu6Y10LS9Qo86+k1HqxTjBut5ULc1XpCQTMzG0dQNzdC4\nmoTwfPAl2rL34iRF+D7aJmsy9plkuXsOs6qkLEuiKGK/NddVHkuK/YHO6uvMF3M6pZwnwPnlnLvn\nP7hnYow3rLYYMDuzZgo2v7pdWQpWYNgk4fhgHwviyIjRp7ZFvqpqhOfRjY0uqiCOI1L7QPgo+l5T\nHW37sDCmumN2OMmnlGVF37YP4lC+RyAj8pnJEMuqpm9bBj1KyDZkswmdPb6XZU2WRjx6Yihdv/Y3\nf4M0zanLwjVvPP/wO1xePmZkgyRpSh9rbuzxPfAk51dXTuRqdX9DXR5R9lSg2w4pBN0w2loFnF08\nMkVS24E3e3RJHEbO0QUhWS7OHRMhDEPiOHETKUoThkGxH3f9tqMoSs7OJetbw2aQkWHXjHKtgxbc\nrzYuO07ThDiQ46kZT7Qcy8KZJxRlQZzPyKYTl/X7QUQoA1fBX93dUxdHAvsas2VI1/Z4sd0AfI++\nfWiDbtuWpjgyXdqTSBTSW1hmahuL0Aq0JkrG7kiNj3bmykegaTvHvPEHxe7+hslYyPqI0Bg3oiEb\nm6oGwjCisxuq50k265U7HQovYLJ8jLYNaGhNmGVUxx3Li5EA5hGEAa3dneaPHpMkiWsr94RASs9A\nfIBCkcbxa+JoAhk8ZPjC900h3YPGUtyGrjVSAJapobQyJIBRyjYI6drCUVWbqiTNMzJbOFRK0VQF\ngZTEiS0m+gGDGtxiLIAgiDkc7YK039MPPa29zrPJgggcA2i9WpFdPaXXmrU1hX61vuXm1XN0Pypi\nRsRp7pQmlVKs1ndOHnpQik5Aa+fVH3zrA+ZJQm43nfnFI6IoxO9DUktP9VJNHEW8vDbze7vZGakA\nm4BM05j1ZutsBLu2o+87xzaLwoBu6JFRQz9YuqoaUF3vEjrhSYaup7G00M16gx+ETnQQhiIOAAAg\nAElEQVRQSg883zDXgCiMyGYBXhgj5ci2OVI2lfsbF7MJ4aMzR/5QWvMn/CGfJE7iXKc4xSlO8ZbE\nG7egG4VxZpOUrmlYWM0UrZXzEwRYLhfExYFXr+7oRx/CPGe93Tl99Gmek8cJYWitm9oO3ZlWZYBB\nK1PEs/j3MPQkacJ0mnK0nGTdK+qqpHpV2t8xvNCxzKeUR7E7kCSjAcCEv/lrf5v33/8JwJhGr+9e\n8eLZn7oipu/7BBLXfCREQKchtVou09kUIQQ3t4bGPzQd2WRObSGAY7VCeD6hNZEtiiN91xNN5mS5\nwXCVhqrTTjRsMsnsNZtMIPQgyzJW9yYjuikLdrsdNiFC1R0yitBoJta8OkszimLv2qk94VGWtatB\nqK7n2D1gvodiR11XCPvKeT5jUIO1xrNYcqc5HLYuq6zKisXyzGUsfdeTxIk7mZFmVGXhKF2eFxHH\nEVOLCQ9dh/R8tA6c9GpV1WgtyGzW7+mBsjw6jRnfMzK9ma17NHXJ1dVjPPnxBhdBFOO3Ndoee5u6\nNJxnf5SulaAH5wMp0xlNeWS5vLS3EeMrbYy3LYx4f3vDo8sr0lFfZ76kKh5OdmroaevW1XdkEBhh\nMwtXVXVJ23UU1lxBo1nOl+x3G9dgI/Csprrle9cN/TC49nGhjdXaSKNTWnN3d09uewkEHnXbsJwv\n2I9F0MOBMEpdE5X0IJmFaCfKdsH97TWFbXq7eHTFdHnunue2KqjKgjCIeWT9PAPPp1YDtX0Oy92e\nsiwdnu0LQeBJZDDWUhqkB9Wom681L7d7pGc+v1Q+qQ95ElGPrfthTJLnXCzMc9dqj9X6wXZw29VM\n85x7+7WiKOm6gWxi5n+PRAQBwhMPHPFB03YDpcW1hacMvXA8RWkIo47Anga71pjhHPbmZBxa/SSF\ncDW0SksIctLQQptRQpAk7tneWH+HTxJvdEH3PMHVmRncwPPZNB0rq+3w6GyO9IRrKPGEOepFccJu\nPxYHa2bTqTPA7ZqWzX7vGgGiJKRuelK7+CZZTN22Tpu7HwR5ErFdFxR7s3jq0GoyW2U+GYYozyOz\nDTxRKEEppraq/XN/7eeZzc757ofGmGO7vaevWoTg4aEQBjIaoQvf98mj2GnSCA2BL+hGkSt67l9+\n6BaPOJvSVAennJjOzshmS4IoIbDH8b7rkaF02iG9UnhKGRU7DOdZBJHDa4/7NUn42u9nEUprwjh1\nuuJFXXN+funUF5VWPLm8cNBQWZU0TeM2VITxaXSMCQRZPiMKExr7N5q6QfCgIOhJH4HnahJxHNI1\n3XgbVGVB0zREdvPztGK3unVuOHEc4/vmCLuzDVGeEMhQOrjJ9yVN1xPaRU1oQd00aCtylGUpg+fT\nWkz9o6Iv9wRS0ttNNphO8IVgYhUx8Xx037jFGCnJkyWJrTcEYYQQ2hzn7ZyeLc8pytLdixoMUWBs\nNNpvd8SJILXuQVJKurpikGbxqJuOfVk4cbQATdPUJElKf9zan1F4XurIBtv1hul06rT5m6ambSq2\nFv5r+47JfMlhb3jTSZaRxgn367Wr4VRVT5aFrh8km+SkSUgozQaplaLtzumUZYLsd3i+JLLsnPf/\ntZ+j70puXj535t9Pn36RoijpbWH6+bMPOBwL90ykScJ+v6PWY81toOlKZ/qgtWBAoOym8mp3h/R8\nLjhzRtR+13J7fe0g1/lsxhcfP+Fosf+irOjUw+antSCMQwTmGg77van/yMAYlWP6ObQGMbLFhADf\nd6JsWmu6Hvb7sbmxM8betsBcC0FXN2jxWgNfkhDFiVOr3Dc9x3pPZIuzsU3sPkm80QVdayj2Y+t/\nzmI+ccLwh/2OKAqZW5nUbhDgNXjSI4is0mEYMoBrq51lOXmeEbt26h4ZDqxswXNXlWg9uOo7g2Z9\nc4/qFZOpeWjiMCCMYucqc7QGF2M7e5hG/NIv/VucW+qZEPDsu992hdauaomSgDRJH9T+RMh0OnEV\n+vnijKF5UDUUQ0fdtKYYCqyun1E1HYvHpoklySY8++Yf41sH+bquiLK5YQDZhc/zwMNzdEoPwHto\nooqSFDXgZIKbqjJdb7YTScoQ1WuqpnNiRHEQ0vUDj2zF/mw5JwwC12nXDwNxmjr8EK1J04xQjo5H\nA1VbM+iH9yhJY+qy4GglCuIoNrixvU6DtWs2tvDtyxB/eLAv2+22+HFKY8cyiiJj6pCmriszSmKa\ntn3ISvcrgiilsh3DIs1QSjwwFerSONX/ANEjmWS0hzX51NRK+rZHSo/WtnBHcU4+mbrMWKsOz/MZ\nDxrDYFyT2kbR2kVf+iEiepCNaIeepuvpbUFyOssZ1OAWY3oBGsfekb5PKHxK++19VeF5FVJ65FOT\n+XI8ItAM9jWFEOy22wc8Fg3aw7PJRhjENFXlai11XZFNcpIwprYnziSSFLs13Si+NXS0dUwytsjX\nDXGckNiFVAjNfLGksIqOTVtTHSsuL9+hG7tNu9qOn3kOvzo9wwsj7q087np1SxAlTr5YepLrm5eu\neQ+lqIrSqY92VYWSAc+vX8DY6ZkkfOHikomlE/sCVvs9j2whdTGdGDG5Ue0SwWw2YWcN5BMfUD2e\nqpzphdY9TdcxWDUuL4rplXbm654QeIFHnpuxiYKI/WZDYed/03S0XU/fdq6zualK+iTFG2m20kNp\n6GyitTk8dIz/sDhh6Kc4xSlO8ZbEG83Q0ZrZ3Bylj0VJlsZOQyVNE+I4dFztyXSK0BEbBKk9cuR5\nCsLgWABl3+B1PsLiaF1dU3c9g21Fz7KAKIgdTtf1PYEvSWepE7Fq2xalGke9C0NJNp0wtZDAL/zi\nrxJHMXevTKVcoJFBQD5qdqQ5WvSEQUCSG5zX80Ljd2g/932PwfNp6lEL/sj9zXM2a3PsXT7+EmeL\nwEEGx+OBy/d+gsJmcvP5GWCs4oSlDoSB0UYfdcI9zyMIQ4f1tV3HdrtxFEMZxHhB7LjtUaSpGqOr\nsrAwwmSSMZvPHO88jiPQ2kFcnueb1xyzP4Tx1hSj7ZrBruUspLeCaVmesl7dmmo/hvHTDYMTMzKk\nEYVvs2chBJ7vsRntzoKAIAgJbDYYJkZPZnN3i2+zTF017A9bhm7ETiVNXTtjiVYaKuWI4w9dw357\nz+bVczsx/xbfG4HvGRkCezz3pU8QTp1GeF2VhEHgDETqoqc47ons98Mko+s7hGWIgJl/URC400nX\nNvhhyM5mb0poY6pgj/zdsafrFHOrCSQ8A11FkRnLKPSpmoZJmDv2UxJlRrp5LAJphULQNdbEIYzw\nPB9pnZGPhwOdMvx/MMJe1y+e8+Tpuw8wVxgQxClGMRu+++GH7H3h/D8n+QRfesRWEyVOUpqmxreU\n2qePrkh3G168fM6F5ZkrrdBqQNnXrduGru15ZJuT4jylansqK2mAJ1ieX1DYU9f96t7oAtl5VhUH\nqu2OummcQfOx77gNQgZh2UxDQxTGtBbr74aBdDJnaftc9qsVh93RSQU0TQsiIgqlY6DJuiFW2jWl\nFVVNFMUspqMnAGgpCKxRdRhImM1cQ9TNqxsCBN0wOBOYR4s5WTbhMEozRxGTJHPzIPDkJ+S4vOmi\nqNY8s4T80PPY7rYko7uI9Djz5kS2oWS729P0itl8QWChh0mWsD/s0ZZLXdYDx93RFU2FF+BFEZNR\n4yOM8dB01pRA655ORNTDw43rQeEJhW8LUdFkyi//8q+QROYN8jwQqie2sM+AJgqMoQUYPLZtO2az\nJbGlV3Z1hxZwtMWrNMjo6j2l1Yi4ef6n7A4Fnj/SA32jGGk3mV75aBRJlLpxC3wfXwtq+zfQih7v\nwZW+b1BKsLNiUp4MOB725LaIGnoe9OaIDdD3migICYRZyAHOFgvmizmBxQ2G3hStxk1id9iRJbnT\nL/E9iRTC6HxjRMV834dBEYdmgdnd30JfP2wKkylJHDhqWFVWaKWNNjVmU6ibGl+MZiEpoR+Yv4tp\nkCqLEjzpfBsFRnwsSG1LnYZu6NnYjkyxFfR95zjlq9tnbO7uOK5e8XERp1O6riO0hdPACxjahuO4\nmckQ3fduQRqGgaZt2R3M35wtz4mznMl0wdo2mAWeZFcUNBa66LqGLE2Z28ah0fBA+g9wkwwTCksP\nlIGRv5K2yO+JgEAG+AjXeau1Zmg7V4vSWqO1do1bwvM5VqUbO08G+EoR2PlvaHsBx2PJSLvt44Tc\n96jsPEgin6J80Hnf7jYkYUKhbL3BgyCOnKjeZr+l70ziMJlak+eqZDZ7RGn15mda03WN80OYFVO0\np2nsXGuamqbpKfZm87uYL2nqmtpi8E3dcb9Zsbm9cRTOvu/YHPes7TOR+CFSRpxbGmkWCA6rlevN\nmEnBi2NLNVISfd802vk5TTOapfR4SrlE6enlJXEUM7ULem/F50bt+DRLiXyPzi7oZ7MZz69vkPcr\n54e6TELms5jEjvd0lrE/FjT2NcZGqU8SbzZDByZW2jaUPruDQtvFd5JnJlOwb0YYRkympi1Z2kV/\nuz9w2B9dptX1A0PfE9riy4CwAmBjtl0ReoLaLiZhnJElGXQN2jYsJEmMH0bMFgZX+8Vf/BWCMHKN\nRaBoVU9mi3RhYAqRocXyBnwWZ3P6fuDVjbHX6xEkUUI2dqgWW549+8DJvQZBQDK94MwqtnlBzOFw\nZDYzn7flERnGjt3QDz2DUkRhyLG0glPaY0AblxsgzedsVrcobVuM+4Hz5dIJD/Vdz/qwdwWiPEuZ\n5Dl5njKxp5Hlco6U0rkH1XVNGCcMejT/iPFl4DKzs/mS4TUlRSkDwmBC17Wu9b/tG7wgIotG1kvH\noNQIc5rGLiEeWuYx8gDaijJFQUiSxI7XLoOAMJC0rXTNRjLwmQZLJwmB1kRqcAJVQRBxPGzpLA7f\n94qhqZz64keG7xOlE2eAvV+/Il9ccvHUYOrXL75LlDw0QPVdz9D3CGtUXRy2xElqWEA20x2EwpM+\nZ1Yhc2hb2vZBybMsSnQ/ODZJkmXEUeLMwDs1oJRyGX/RlEbAa8DZGaZJSpgYC0czNhJP+mzsphJG\nMbf393TWrNlHMfQtjV3U6rY2ip6+dqeTi/ycrh/w7Zs2CUK2+yPKFjibViFnkguLTRe7DYf9HmHF\n5QYtmM6XhMPgsOh+GDgcj07WtzweSaYTStugk2UTPOnh+Q82jL3quHryrn2NNS9fPGcamM2wOJYs\nFkue+wHKbsK7zYqqPLqmwa6qEb7nPh9kQnE4UhW2STCQPJ1FdDbr//b9Bl+GVG3tkpYgDGjKktQS\nHCZJQpzGDLbukaQZJIpsbCrsG3ylCcd6je/x3uUFzXzC8+8Y0sMsjmj2B4LRxKVtOMtjthvzrAf+\nJ5fAOmHopzjFKU7xlsQbzdAD3ycJRiYIXJ4vncfl/eZAmMSktmNwu9sy61Pu7+8dh7YoKgalHAvg\n8vIRq/XKdZMFcUxddQ62aY4NhLFjyeT5FIYB5flkVnJgPp/xV3/6r5NbqmOexDS6o7ZYdR4mXFxc\nuiwKYDo/52AznvXqjqo2DJLKfk17guU7TykO5vNXL59TNAqFyUK9KGO2WFAUJvtLJglJmlBavHA2\nnVJXtcPUwZgR7457l72loUddFAhbGW+bkiD0kWFmxzqmrUtGtRJPBszmqRNHOl9MeHR5icKYGpgL\nN+yI2rYgK6XZ7/ZIS58aeoGHJrXYdd/3KAWxPXX1XUdV1can0Y5nlhmJ2dEgwGiE+M6nNAgkalDu\nOL/d7+i7gUfWkzEMApI4ZnVvTj8a39D52tpJwHrS6IaPVoN1cWS33dKMzI3iSJwkDKPWiy9p6tJp\niH9UXL94hgICC1XoASgP+LeGhbFf39J7D1K2TdvSaxisJPJhdc+gNMtHV46Z0XcKoaGtRlqoBgS+\nZVmkecZ+fU9pcWJPCIruaOipGLaLgQPGDkJlbAHTnEhbA+yqxhOe6xQV0qesCkr7jKzXa7TCQVpp\nntM3tZNZ9oOQqqgQKB49Mu+B5wuGunZ1kEFLzh9d0I/zZFBkWUhin7MNkvPLJY29j+fPPuDV7TWL\n+RLfZrZxlFAUR3zL+c5mC/qmJrMnDdUrssmEldVkD1AIhOvUXcwfIYOMtjJZbBEU9L1i+VPnFHau\nvcoz2qEzssdAeTgynywoLBRXVhXHQ0E3wjq+B0GIas1rPMkiwtC88nML9cwmOeWxYIjMXMqbhkb3\npNZvNY5i6qaitofFNJ8itHIWjKpXFMOWAc1Xv/YVM7e0RoGT6Baeh1IDoaUgR/4nz7vfOOQy8qCj\nKOT2fsc4k6aznKKsuL6x2tCex3q9NYuW/ZksiYybu23LX62M0e94mgk8yXw+dcc4gHgy4cmVmZhD\n16NUS9fWrgHkx378q+RJTGjbxrfVniAI+NIXjUaHFJIkSaltwUIL2KxW1gwCPD/A9yWqH4wNEDCb\nzqjrmsI2BMRRQtdUXPzVnwFAaE3X9ly+Y47eSinCMGJvedW3N3emOCjH4ldMEHrMkpnzLkzyGdv1\nxjUwKG341qNkwXa/Zr44p7dqdZ4HWT4jsefNs8UCrZTxS7QP8+r2FfgRQWTGL5ABGgN1gcEkk3zi\njo9t0yLCkN5eVF0UNG1Hmk9ckVmpgUD6CDs5tRB4COrmQTc8DCJ22/GBmaOFcLriSZqxOxwQFl/u\nhxZPeUYjxo5P17Qo4blFCk+yWF7QjEbTWYbS6kEXf6hJJxOa8vsbNn7nP/6PzOuu7oizDN9SMj0v\n5FBU6Ni68sgMbxgc/CE9gfI8p/USJwnHzQrpBSS2p6HTGukHRGKcn0bnfrwPX/jMF+fOOMIPJEIY\n6AtMEfp4bGgsXDKfL4mThLKsHPVO6cHwpEcK5+FA0/eukUt2PQKBsD9fVjV66Fw7fN/UhFHIJJ8y\nta7zdduTZFPXpIbwjOHK2APRN9R7ze3WPCNVWSCDyEFzIknxe01Rt+i1LXbLgMV84Yqxm9tbBuHz\n6PETANI84rjfMrH+CHfX1/R45Lbeo4aOSSppQ7OhTvI5Sg1cv3ruagzLfEHdNmytjkRyMaUq9syv\nzGt4Vh4isz6lvYxZrW9R9j3dK03gNaSR5KlNWrq25Tzyubfzt64bYiJ6aTbp9XbP1aNzkth8vtnu\n2e/3blOP44TpxRV+eWB7b4qzeZKCLx2MozHPazDCUcXHaw59b7xZHrqA67VZtGbTGa3STja13h7Q\nWhNb3NlTivVuz3J5Rm8nZ9eYbrHMKqxFcUieJgZLxjjARDJ0RY3JfMkX3vuiMz7QoqfrNT/zs3/D\ndRUKMVA1JY3lZ3/5x77CbL5ksLtlmiQoPeBbfPa7L56xWJxz+dhsEn3XUWzX9E3tMr6ua+m7Dmmz\n6eN+jw4S8hGHjwKE8J2D0fWLZ9ysVhztwik9yfJswdgVJMMALQSD1o4vvF+vYVDsbdNVNl+gPSh2\n1liiU+hD4bjwcZ7TdWuW7xkMsqpK/DjB7xW7nZlYx8OB8/OErc2Go3xJ39ROfc4PpOFC24lX1RWh\n0NRHsxjf3d2S5BNWty+Z2MxL4KG0cu5M2SRjd3/n5FyHvkcGkollBAWRJI5jh/H21ZE4jNBOvdED\n4bksFkBGPkJ4biO/vn5OEqeOiw2CY1U4Q4wkSdBd6TbM16OrrIlDUyKlTx8/1CimSeKahLwwpFPa\nnPowi5oeeifRm0zPuauesbp7ycRmgLPFGZ4nXKOblD54Es8+hlJKc82jPoywan62DhKnCXGSOPcc\nIUAIjySN6a2ejuf7xiTbZs/73YFu6Fx/R5YaZ5xRmKzpe6QMmdh6TtDUtHXJ4bB3vQS661hePGI2\nm9t77UnsJgnQ1DWT2ZLvPDMiZF7rcTwe3MktCVOixcQqS9pQPXV5dO/J4vKCVy+vTVIBTKYLjts1\n/cgWiXOyIHjoD5E+96uN684GkHHOfH5OkpqfOfMEx6IksJSf3XZDluRUdhOJw5B3f+zLtHYubVe3\nzGcz94x5MqQsDxRtT2/Xh2kcotuW88BuwnXJEEfU9n0/VqUp/I7d6UIzDAPpaFbRlGxeFXRKmcY/\njOlFFgaOjUeYEMiAaDYmDx9/kvzeOGHopzjFKU7xlsQbzdAHpd2Oent/i5QSYTOvMJJI36O1rb1C\nC2bzOVGSOg/ANIlg6KkdD1pTdz213XG9oSOZTJlZGtjjp4/pu84dWcMg5md+9qeIZMyhtNlwEvH+\nl36MJ1cmcw2CAM/z8Wz3qdIDm7s7Bytcnl+R56nLiI6bFXe3LwmjxBkqoFv63rA5AJIkp6srqsPY\nDjwhSQJuX5njZ1F3SE861ksSx3Rt7VgFQzvQ4TOoznlv6qYhThK0Z7sOuw4ZhA7SaurKsFXssdj3\nAlAD642hcDXWKESrnosLA/3M50vz9y3DpK4r05k5dqN63p/xOZ0u5oRRxN5iGZcyYLffgwwdM6Yp\njqRZ+mCOrDXJbIbV7uew3RL4HmMS0rUdnvCQ9hqOh4oYgWcz/GFQtF1D3/VO3jUMjLLkyDSIYyOn\n62SWfY84TNhYcwqER3r5PkXx/exeJUYDkJbqsHFSq/f3a2Znj0js6TCXPtVhzY2FKuI0Ic6nHKya\nZbldm+vwpTHcAA7Hkrbb4dvMbHl+hkYYBUAgjjTS9919VFVFlucctgaGPO4PRjP9NQy9Hzo84Tvf\nV4U2tRc9moPnNG3t6lBJlpHlE/b2fUz6zmb6D+3vfhgTypzCnv7SKEK1PfGolYOgKmsmlq8d5wH3\n96/IrKaSn+UoPSBH6FP4CN2jlXZ2e5MsQ5cVscWihSe4eucppT2lHrb3LC8uKS3leLW5RwhBNrbB\n64Asm9EKW5vpO66vnzGZL5g7yznJfDJ1lpTFoeDli2cc7bNfFAVKDUgLiS3DiP7VK6dE6cuAqb/g\nWFY0vaVHCh+SlKldt/breyINhf2d2XLJd559lyfWO1krTVEWeDZjD6OQpqpBa462Q/jyYokiQlgq\nb1+X6NZztaxj9fG6/d8bb7YoKn2+8NRAFU1VUQwDjcW3VFlDGDCxBbpJnhNKn6rp8EZ5gN0W4XlO\nJ0QLD19KMivwhZD0GgJ7RO0GxVBXYCVNf/KrP01dNzRCMD032NxXf/wnyZOcwMIKQRjQNo0zZr25\nucaTCaHlwvddyeFQU9g3o+96ZosLDptb4rlZkH1fGnrZaLTRdzx95z2DswN+HFPVNbVdnLM0o6kq\nsnQ08ihp+4HIcsb3ZQG+wZUnVuu9aCp6Xzp+9m69QRPQWV5umiUk2QNnXHo9WgdUjbmG1c0dy7Nz\nqqKizk0RaF0XCOmT2fvwPGmOju04/muu3n2P2BadtVZsN1vnCLXerDkcChbLM1dkmy7mxijANknd\nXF8zmc2ckYkOQgYRuo0nTUO6rnNFvYvLK4rdmr0VUIrTFKXBk9JcH4YDrrR2G2gcGjPwUSK56VoC\nETC3HpnH4kieZuzD77eCefXCNBtl55eIWOJZgapOHbi9/i653XTPnrwLTcfFxDbfJDnogcTO3/X9\nLZ4nkRInWexXFRrhCtub1YooSV0LfVlXSP9Bz7/teprVylH3hBoQStCNUgBBQCwjqqZ27e5DPxgI\n3i4gcRyR51O05Th7wkj4Jnas7tdGBmFh4ZS2Krm5e8Xjqys8C/k1TcXtqxdc2lqUkWzWHA5WBng+\n5eri0m0au92WY1nRWW58JCVXT5+yvnlBvzdzab+54913v0hqx6s8bg1F2e7sXhKz396ztRBtkk9o\nutZtfk3TkGY5775nal2b9T3zrufs/BHFKKTVKWQgXZNVkqTkszmenXtJNiVOEveMrO5eEacR4WBl\nbeOE/f0tiT8QCfOe7A4HlBRsbHH2nbMLkjRzEtTlfk+cxuxfmOI5WU5XN5QWDCkOBd3Q0dQPOkAX\nl1fsi4a5Xcf6fmC9Obp5MV7vJ4k3uqD7QnBc2SzJk6iu5cxm01EYoNRD4Up3Dbuyp+8Ht3jWVUU2\nnZHYBhIRyAdLNWBoalNltqI3W/Z89Se/4lTNDnXJcr7kC194j7lVGEyjhMNxTazMYlpWFUppYpsR\nhnEOQ8/dteGMRklCXzdEiZmI88WcV8++TZQ+uImjTDdp+JqoTlnXLO1icP3yGfvdnsw66gydEfcq\nbRfn/ngkiCIqK4YURjFt00BT49lFvxsUqixc08lkeU65P5Ja7Ho+H7Fd8wC1bY/nQ227EifzBbv1\nmmQ6IbUT6cXzD7m6+gKhzSD9MCQKIyo7edN8hhTSdeoeDntm87kzY2ZQPHn81DBXbGFpXGRH410Z\nBdzf3TnXumw6IwqE0+PxAomvBm5vzAPR9j1K+M7yL9SaUAh6NEdbLIriCK+rnQn3MPQUVUFp7eEQ\nA23HQ1et70MyoRi+f/ofVkYBsysPqMfvcX71jvmd4xqvLegrM/7N5p4ozVw2t727IYgyGnuS8z3J\n7rij3u/pxahF7pNO5ihbdD7uazR6bA0gDGP0a+9ZGIcIjeue9qWkrCqHqQdBYPowwtBx1WUUMuiB\nYTQE8Q0uP463DCS+5xN6Zq4+Wiy5bVvubsx9F+URH4+bly9ZWmVEEacgNN/68LvudZ9cXpluaKCq\nGnPatve5Lw6ESUJqGVdV1fCd5y949wvv4afWwP322jQn2cLpNJ+ShJ4rvK63e/LpgsdPzfhXxR4G\nTW+TuzjJ6JuSVpm526Hwo4RXL1464kA+y2jKBv0asBxHqdMhV1ohpeDuzmb5UcoXvnzpDF9evXzO\n9PIJbVUSjfX2+4Gyrh3+/Xy95kmYkp+ZzS5OY7yh42CLv/VqjWpaV9PIZ1MmkwkrpV0t5F9+4wPy\n6QQ1OocJj3SSOR+Csnpgu/2wOGHopzjFKU7xlsQbzdDrpmO1NfjVe++9QyqmjBTLpigo6t7pYHdN\njR/6lMfCGSEnuXHCEc5RJKaoWwdtRFFA20FoOaBf+cmvUdQVj85MZvz4yROuHl8hpXS64FoppvnM\n6XerQTB4it4S0JI45MW3v+O+3xYVYRhx2BkIoCqPBKmxmLq9fgZAGKdMZxcUFntVdiAAAAZJSURB\nVA+cLhYMWjksejaZ4nnSKN8BdVMRhoGjRh6292SzC2f9NvQ9XVlSl4U7Sh8OB9p+ILTH87Jq6LRC\nWMilKHziOCEaj/NFw9BWjovdty1dVzENZmysOuXFoycIX7isuq9rttstk9GCzvdp+851gZ6dnTMo\nRW6lhX1fksQRVVUifZNx71c3iDhnOp/Y8dXgJ07y+Pr5d7i6vMIiXKxvCgatjLUXJts+O184ml0W\nhRzrmtuXz1lYS7++7fCzDN/y0meLM7r7V45Vsd3ujK2dZSbM8glVIXjvx7/G98ZjqzR5fXuHvr0m\nsPziQAbsDge8EXvOc5pG0TXmPVxeXDFUNbUdm92+YLVZMfQdkdWXT/RA6CnCsXU/kOi2Yhh9NZUi\nSRJK27kYRgFxAIPlrW9u7zi7usS3Y+v7El/YcbcwTpwk7PY7SsuY8H0P6YUuQx+UYmhbpzwZiICz\n5blzc0qSnGHoubu/527sNvUPZGnkdML10PH8+XeYZIaFESU5Tx4/drBkEqf0Xcv9ZpQ3Djibz9Ft\nxczSg/3zM5OdWzyk6Vv8MGVmtV7KrqPvSnZbqxcznzNZzLl5aU4SVVXy+Ok7vHhpmDXT6RLd75FR\ngmezfq9Xpg5h/VbbrmK5nDmOuIfP/d01w2DmxTLNaIs9M9vJ++SdL1K3LVVZom3W/jSb0jaV8wOV\nux3b+5duvj/N3oEg4OIdU5OrjyXR3Q0rOxa3xwNKeMyXM2b2uoJAsl5vef7cdpficXF56fyAZfzJ\nXaLFiDO+iRBC3AEFcP/GXvRHM845jQGcxmGM0zicxmCMjxuH97TWFz/sl9/ogg4ghPjnWut//Y2+\n6I9YnMbAxGkcTJzG4TQGY/xFx+GEoZ/iFKc4xVsSpwX9FKc4xSnekvgsFvTf/Qxe80ctTmNg4jQO\nJk7jcBqDMf5C4/DGMfRTnOIUpzjFX06cIJdTnOIUp3hL4o0t6EKIXxFCfEMI8S0hxG+9qdf9UQgh\nxHeEEH8ghPg9IcQ/t19bCiH+FyHEN+3/i8/6Oj/NEEL8N0KIWyHEH772tY+9ZyHEb9u58Q0hxL/5\n2Vz1px8fMw5/Xwjxws6H3xNCfP2177114yCEeFcI8b8JIf5YCPFHQoj/wH79czUffsA4fHrzYfQc\n/Mv8B/jAnwLvAyHwL4CvvYnX/lH4B3wHOP+er/2nwG/Zj38L+E8+6+v8lO/5F4CfBf7wh90z8DU7\nJyLgS3au+J/1PfwljsPfB/7uR/zsWzkOwGPgZ+3HE+Bf2Xv9XM2HHzAOn9p8eFMZ+l8DvqW1/rbW\nugX+EfDrb+i1f1Tj14F/YD/+B8C//Rley6ceWuv/A1h/z5c/7p5/HfhHWutGa/0B8C3MnPn/fXzM\nOHxcvJXjoLW+1lr/v/bjA/AnwFM+Z/PhB4zDx8Wfexze1IL+FHj22ufP+cE38raFBv6ZEOL/EUL8\nu/Zrl1rra/vxK+Dys7m0Nxofd8+fx/nx7wshft9CMiPU8NaPgxDii8DPAP8nn+P58D3jAJ/SfDgV\nRd9M/LzW+qeBXwX+PSHEL7z+TW3OV58rutHn8Z5fi/8SAz/+NHAN/Oef7eW8mRBC5MA/Bv5DrfWf\n8f/7PM2HjxiHT20+vKkF/QXw7mufv2O/9rkIrfUL+/8t8D9jjk03QojHAPb/28/uCt9YfNw9f67m\nh9b6Rms9aK0V8F/xcIx+a8dBGFPYfwz8d1rr/8l++XM3Hz5qHD7N+fCmFvT/G/iyEOJLQogQ+A3g\nn76h1/5MQwiRCSEm48fAvwH8Ieb+f9P+2G8C/+SzucI3Gh93z/8U+A0hRCSE+BLwZeD/+gyu743E\nuIjZ+FuY+QBv6TgIY4f0XwN/orX+L1771udqPnzcOHyq8+ENVni/jqnq/inw9z7rivMbvO/3MZXq\nfwH80XjvwBnwvwLfBP4ZsPysr/VTvu//HnN87DDY39/5QfcM/D07N74B/Opnff1/yePw3wJ/APy+\nfWgfv83jAPw8Bk75feD37L+vf97mww8Yh09tPpw6RU9xilOc4i2JU1H0FKc4xSnekjgt6Kc4xSlO\n8ZbEaUE/xSlOcYq3JE4L+ilOcYpTvCVxWtBPcYpTnOItidOCfopTnOIUb0mcFvRTnOIUp3hL4rSg\nn+IUpzjFWxL/H50X5jAIJ3VMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2edaa358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Actual Steering Angle = [-0.09872733]\n",
      "Predicted Steering Angle = [-0.0003692]\n",
      "L1 Error: [ 0.09835813]\n"
     ]
    },
    {
     "data": {
      "image/png": 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HtN6qssZirAnBcSkFSdYLAcA4TpA6QihJ4v9NCoEQEuutfmttCIQCtG1La0zA+AGqugnB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\nQZ8wYcKEe4L/B6Cu+Kiy1yWSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x310717f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "[sample_batch_train_data, sample_batch_test_data] = next(train_generator)\n",
    "predictions = model.predict([sample_batch_train_data[0], sample_batch_train_data[1]])\n",
    "for i in range(0, 3, 1):\n",
    "    draw_image_with_label(sample_batch_train_data[0][i], sample_batch_test_data[i], predictions[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks good! Let's move on to actually running the model with AirSim in the [next notebook](TestModel.ipynb)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
